{"id":1943,"date":"2024-02-19T17:54:25","date_gmt":"2024-02-19T17:54:25","guid":{"rendered":"https:\/\/dessevproject.eu\/?page_id=1943"},"modified":"2024-06-03T09:54:57","modified_gmt":"2024-06-03T09:54:57","slug":"knowledge-base","status":"publish","type":"page","link":"https:\/\/dessevproject.eu\/es\/knowledge-base\/","title":{"rendered":"Base de conocimientos"},"content":{"rendered":"<div data-elementor-type=\"wp-page\" data-elementor-id=\"1943\" class=\"elementor elementor-1943\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-957bf83 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"957bf83\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-no\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-828750f\" data-id=\"828750f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-db418b9 elementor-widget elementor-widget-heading\" data-id=\"db418b9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.10.1 - 17-01-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h1 class=\"elementor-heading-title elementor-size-default\">Base de conocimientos<\/h1>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2cd754e elementor-widget elementor-widget-text-editor\" data-id=\"2cd754e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.10.1 - 17-01-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#818a91;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#818a91;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>Base de conocimientos en forma de<br \/>Reglas b\u00e1sicas \u201cSI\u2026 ENTONCES\u2026\u201d<br \/>que se puede implementar f\u00e1cilmente en el sistema de soporte de decisiones.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f3d3fb3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f3d3fb3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-c7a8999\" data-id=\"c7a8999\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f47a380 elementor-widget elementor-widget-spacer\" data-id=\"f47a380\" data-element_type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.10.1 - 17-01-2023 *\/\n.elementor-column .elementor-spacer-inner{height:var(--spacer-size)}.e-con{--container-widget-width:100%}.e-con-inner>.elementor-widget-spacer,.e-con>.elementor-widget-spacer{width:var(--container-widget-width,var(--spacer-size));--align-self:var(--container-widget-align-self,initial);--flex-shrink:0}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container,.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer,.e-con>.elementor-widget-spacer>.elementor-widget-container,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer{height:100%}.e-con-inner>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner,.e-con>.elementor-widget-spacer>.elementor-widget-container>.elementor-spacer>.elementor-spacer-inner{height:var(--container-widget-height,var(--spacer-size))}<\/style>\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6d2729a elementor-widget elementor-widget-heading\" data-id=\"6d2729a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Selecci\u00f3n de enfermedades<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-85900ea elementor-widget elementor-widget-text-editor\" data-id=\"85900ea\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Bas\u00e1ndose en estad\u00edsticas y datos actuales de las principales organizaciones sanitarias, como la Organizaci\u00f3n Mundial de la Salud (OMS, <a href=\"https:\/\/www.cdc.gov\/nndss\/index.html\">https:\/\/www.cdc.gov\/nndss\/index.html<\/a> acceso el d\u00eda 23 de febrero de 2024) a trav\u00e9s de su Observatorio de Salud Global (GHO), los Centros para el Control y la Prevenci\u00f3n de Enfermedades (CDC, <a href=\"https:\/\/www.cdc.gov\/nndss\/index.html\">https:\/\/www.cdc.gov\/nndss\/index.html<\/a>, acceso antes del d\u00eda 23 de febrero de 2024) a trav\u00e9s del Sistema Nacional de Vigilancia de Enfermedades de Declaraci\u00f3n Obligatoria (NNDSS) y el Centro Europeo para la Prevenci\u00f3n y el Control de Enfermedades (ECDC, <a href=\"https:\/\/atlas.ecdc.europa.eu\/public\/index.aspx\">https:\/\/atlas.ecdc.europa.eu\/public\/index.aspx<\/a> (acceso antes del 23 de febrero de 2023) a trav\u00e9s de su Atlas de Vigilancia de Enfermedades Infecciosas, hemos identificado 22 enfermedades para su an\u00e1lisis y seguimiento concentrados en el marco de este proyecto. Estas enfermedades han sido seleccionadas en funci\u00f3n de su impacto significativo en la salud mundial, su prevalencia y las tendencias observadas en datos recientes, asegurando as\u00ed que nuestro sistema est\u00e9 equipado para manejar enfermedades infecciosas que representan amenazas para las operaciones mar\u00edtimas.<\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"2\">\n<p style=\"text-align: center;\"><strong>Lista de enfermedades seleccionadas<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Varicela<\/p>\n<\/td>\n<td>\n<p>Paperas<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Chikungu\u00f1a<\/p>\n<\/td>\n<td>\n<p>Norovirus<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Colera<\/p>\n<\/td>\n<td>\n<p>Tos ferina<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>COVID-19<\/p>\n<\/td>\n<td>\n<p>Rabia<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Dengue<\/p>\n<\/td>\n<td>\n<p>Rubeola<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Difteria<\/p>\n<\/td>\n<td>\n<p>Tetanos<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>\u00cbbola<\/p>\n<\/td>\n<td>\n<p>Tuberculosis<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Mononucleosis infecciosa<\/p>\n<\/td>\n<td>\n<p>Fiebre tifoidea y paratifoidea<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Gripe<\/p>\n<\/td>\n<td>\n<p>Hepatitis A<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Malaria<\/p>\n<\/td>\n<td>\n<p>Fiebre amarilla<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Infecci\u00f3n meningoc\u00f3cica<\/p>\n<\/td>\n<td>\n<p>Zika<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b6bc67c elementor-widget elementor-widget-heading\" data-id=\"b6bc67c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Adquiriendo conocimientos m\u00e9dicos<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-541639ec elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"541639ec\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-65c6310f\" data-id=\"65c6310f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-59c00d33 elementor-widget elementor-widget-text-editor\" data-id=\"59c00d33\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>En primer lugar, se identificaron las publicaciones pertinentes sobre enfermedades seleccionadas, los criterios de diagn\u00f3stico de diversas infecciones y las directrices para el diagn\u00f3stico de enfermedades infecciosas. La bibliograf\u00eda incluye art\u00edculos internacionales revisados \u200b\u200bpor pares, informes en l\u00ednea, comentarios, editoriales, libros electr\u00f3nicos y comunicados de prensa de universidades e instituciones de investigaci\u00f3n, que incluyen opiniones de expertos. Tambi\u00e9n se incluy\u00f3 la literatura gris publicada por la OMS, los Centros para el Control y la Prevenci\u00f3n de Enfermedades (CDC) de los Estados Unidos y otras publicaciones y medios de informaci\u00f3n de los gobiernos locales. Las bases de datos de investigaci\u00f3n examinadas incluyeron PubMed, Google Scholar, Embase, Medline y Science Direct.<!-- \/wp:html --><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fef1119 elementor-widget elementor-widget-accordion\" data-id=\"fef1119\" data-element_type=\"widget\" data-widget_type=\"accordion.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.10.1 - 17-01-2023 *\/\n.elementor-accordion{text-align:left}.elementor-accordion .elementor-accordion-item{border:1px solid #d4d4d4}.elementor-accordion .elementor-accordion-item+.elementor-accordion-item{border-top:none}.elementor-accordion .elementor-tab-title{margin:0;padding:15px 20px;font-weight:700;line-height:1;cursor:pointer;outline:none}.elementor-accordion .elementor-tab-title .elementor-accordion-icon{display:inline-block;width:1.5em}.elementor-accordion .elementor-tab-title .elementor-accordion-icon svg{width:1em;height:1em}.elementor-accordion .elementor-tab-title .elementor-accordion-icon.elementor-accordion-icon-right{float:right;text-align:right}.elementor-accordion .elementor-tab-title .elementor-accordion-icon.elementor-accordion-icon-left{float:left;text-align:left}.elementor-accordion .elementor-tab-title .elementor-accordion-icon .elementor-accordion-icon-closed{display:block}.elementor-accordion .elementor-tab-title .elementor-accordion-icon .elementor-accordion-icon-opened,.elementor-accordion .elementor-tab-title.elementor-active .elementor-accordion-icon-closed{display:none}.elementor-accordion .elementor-tab-title.elementor-active .elementor-accordion-icon-opened{display:block}.elementor-accordion .elementor-tab-content{display:none;padding:15px 20px;border-top:1px solid #d4d4d4}@media (max-width:767px){.elementor-accordion .elementor-tab-title{padding:12px 15px}.elementor-accordion .elementor-tab-title .elementor-accordion-icon{width:1.2em}.elementor-accordion .elementor-tab-content{padding:7px 15px}}.e-con-inner>.elementor-widget-accordion,.e-con>.elementor-widget-accordion{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-accordion\" role=\"tablist\">\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2671\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"tab\" aria-controls=\"elementor-tab-content-2671\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" href=\"\"><\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2671\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-2671\"><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2672\" class=\"elementor-tab-title\" data-tab=\"2\" role=\"tab\" aria-controls=\"elementor-tab-content-2672\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" href=\"\">Literatura (haga clic para abrir\/cerrar la lista)<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2672\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-2672\"><p><a target=\"\">Chickenpox: presentation and complications in adults<\/a> Abro AH, Ustadi AM, Das K, Abdou AM, Hussaini HS, Chandra FS.<br \/><a target=\"\">Clinical manifestations, complications and management of chickenpox infection in pediatric<\/a> Bereda G.\u00a0<br \/><a target=\"\">Chickenpox Clinical Presentation<\/a> Anthony J Papadopoulos, MD<br \/><a target=\"\">Interna Szczeklika 2022<\/a> Group work<br \/><a target=\"\">Chronic Joint Pain 3 Years after Chikungunya Virus Infection Largely Characterized by Relapsing-remitting Symptoms<\/a> Sarah R.\u00a0Tritsch,\u00a0Liliana\u00a0Encinales,\u00a0Nelly\u00a0Pacheco, et al.\u00a0<br \/><a target=\"\">Manifestations of Atypical Symptoms of Chikungunya during the Dhaka Outbreak (2017) in Bangladesh<\/a> Deeba IM, Hasan MM, Al Mosabbir A, Siam MHB, Islam MS, Raheem E, Hossain MS.<br \/><a target=\"\">Overview on Chikungunya Virus Infection: From Epidemiology to State-of-the-Art Experimental Models<\/a> Constant LEC, Rajsfus BF, Carneiro PH, Sisnande T, Mohana-Borges R and Allonso D<br \/><a target=\"\">Chikungunya virus: A general overview<\/a> K.A. Gal\u00e1n-Huerta, A.M. Rivas-Estilla, I. Fern\u00e1ndez-Salas, J.A. Farfan-Ale, J. Ramos-Jim\u00e9nez<br \/><a target=\"\">Chikungunya virus disease<\/a> European Centre for Disease Prevention and Control (ECDC) 2024<br \/><a target=\"\">Parazytologia medyczna kompendium<\/a> Morozinska- Gogol<br \/><a target=\"\">A prolonged, community-wide cholera outbreak associated with drinking water contaminated by sewage in Kasese District, western Uganda<\/a> Kwesiga, B., Pande, G., Ario, A.R.\u00a0et al.\u00a0<br \/><a target=\"\">Cholera \u2014 the new strike of an old foe<\/a> Anna Kuna, Micha\u0142 Gajewski<br \/><a target=\"\">Colera<\/a> Matthew Fanous;\u00a0Kevin C. King<br \/><a target=\"\">Sensitivity, Specificity, and Public-Health Utility of Clinical Case Definitions Based on the Signs and Symptoms of Cholera in Africa<\/a> Nadri J, Sauvageot D, Njanpop-Lafourcade BM, Baltazar CS et al.\u00a0<br \/><a target=\"\">Factsheet on COVID-19<\/a> European Centre for Disease Prevention and Control (ECDC) 2024<br \/><a target=\"\">COVID-19 diagnosis and management: a comprehensive review<\/a> Pascarella\u00a0G,\u00a0Strumia\u00a0A,\u00a0Piliego\u00a0C,\u00a0Bruno\u00a0F et al.\u00a0<br \/><a target=\"\">COVID-19 patients&#8217; clinical characteristics, discharge rate, and fatality rate of meta-analysis<\/a> Li\u00a0L-q,\u00a0Huang\u00a0T,\u00a0Wang\u00a0Y-q, et al.\u00a0<br \/><a target=\"\">Clinical profile of Dengue fever in an urban tertiary care hospital in South India<\/a> Dhivya P., Monica A., Jayaramachandran S.<br \/><a target=\"\">Dengue\u2014How Best to Classify It<\/a> Anon Srikiatkhachorn, Alan L. Rothman, Robert V. Gibbons et al.\u00a0<br \/><a target=\"\">Dengue hemorrhagic fever \u2013 A systemic literature review of current perspectives on pathogenesis, prevention and control<\/a> Wen-Hung Wang, Aspiro Nayim Urbina, Max R. Chang et al.\u00a0<br \/><a target=\"\">Clinical Characteristics and Management of 676 Hospitalized Diphtheria Cases, Kyrgyz Republic, 1995<\/a> R. Kadirova, H. \u00dc. Kartoglu, P. M. Strebel<br \/><a target=\"\">Corynebacterium Diphtheriae<\/a> Anmol Chaudhary;\u00a0Shivlal Pandey<br \/><a target=\"\">Association of clinical signs and symptoms of Ebola viral disease with case fatality: a systematic review and meta-analysis<\/a> Harsha\u00a0Moole\u00a0,\u00a0Swetha\u00a0Chitta\u00a0,\u00a0Darlyn\u00a0Victor et al.\u00a0<br \/><a target=\"\">Clinical Manifestations and Laboratory Diagnosis of Ebola Virus Infection.<\/a> Qureshi AI.\u00a0<br \/><a target=\"\">The Reemergence of Ebola Hemorrhagic Fever, Democratic Republic of the Congo, 1995\u00a0<\/a> Ali S. Khan, F. Kweteminga Tshioko, David L. Heymann et al.\u00a0<br \/><a target=\"\">Acute and Chronic Symptoms of Mononucleosis<\/a> Sanjay Lambore, MB, MSc, James McSherry, MB ChB, and Arthur S. Kraus, ScD<br \/><a target=\"\">Infectious mononucleosis in children \u2013 one centre experience<\/a> Joanna Maria Wrembel, Tomasz Jarmoli\u0144ski<br \/><a target=\"\">Clinical Signs and Symptoms Predicting Influenza Infection<\/a> Monto AS,\u00a0Gravenstein S,\u00a0Elliott M,\u00a0Colopy M,\u00a0Schweinle J.\u00a0<br \/><a target=\"\">An Office-Based Approach to Influenza: Clinical Diagnosis and Laboratory Testing<\/a> NORMAN J. MONTALTO, D.O.<br \/><a target=\"\">Travelers Malaria<\/a> Patricia Schlagenhauf-Lawlor<br \/><a target=\"\">Sensitivity of fever for diagnosis of clinical malaria in a Kenyan area of unstable, low malaria transmission.<\/a> utanda, Albino &amp; Cheruiyot, Priscah &amp; Hodges, James &amp; Ayodo, George &amp; Odero, Wilson &amp; John, Chandy<br \/><a target=\"\">Plasmodium falciparum clinical malaria in Dielmo, a holoendemic area in Senegal: No influence of acquired immunity on initial symptomatology and severity of malaria attacks<\/a> Rogier, Christophe &amp; Ly, Alioune &amp; Adama, Tall &amp; Ciss\u00e9, Badara &amp; Trape, J.<br \/><a target=\"\">Invasive Meningococcal Infection: Analysis of 110 cases from a Tertiary Care Centre in North East India<\/a> Dass Hazarika, R., Deka, N.M., Khyriem, A.B.\u00a0et al.<br \/><a target=\"\">Which early \u2018red flag\u2019 symptoms identify children with meningococcal disease in primary care?<\/a> Tanya Ali Haj-Hassan,\u00a0Matthew J Thompson,\u00a0Richard T Mayon-White et al.\u00a0<br \/><a target=\"\">Mumps Virus: Modification of the Identify-Isolate-Inform Tool for Frontline Healthcare Providers<\/a> Koenig KL, Shastry S, Mzahim B, Almadhyan A, Burns MJ.\u00a0<br \/><a target=\"\">Characteristics of a large mumps outbreak: Clinical severity, complications and association with vaccination status of mumps outbreak cases<\/a> Stein\u00a0Zamir,\u00a0H\u00a0Schroeder,\u00a0H\u00a0Shoob,\u00a0N\u00a0Abramson\u00a0&amp;\u00a0G\u00a0Zentner\u00a0<br \/><a target=\"\">Mumps outbreak and laboratory diagnosis<\/a> Myl\u00e8ne Maillet, Eric Bouvat, Nicole Robert et al.\u00a0<br \/><a target=\"\">An outbreak of norovirus-related acute gastroenteritis associated with delivery food in Guangzhou, southern China\u00a0<\/a> Lu Y, Ma M, Wang H, Wang D, Chen C, Jing Q, Geng J, Li T, Zhang Z, Yang Z.\u00a0<br \/><a id=\"10.1371\/journal.pone.0143759''\" target=\"\"><\/a>Vomiting as a Symptom and Transmission Risk in Norovirus Illness: Evidence from Human Challenge Studies Amy E. Kirby, Ashleigh Streby, Christine L. Moe<br \/><a target=\"\">Clinical Manifestation of Norovirus Gastroenteritis in Health Care Settings<\/a> Ben A. Lopman, Mark H. Reacher, Ian B. Vipond, Joyshri Sarangi, David W. G. Brown<br \/><a target=\"\">Clinical manifestation of norovirus infection in children aged less than five years old admitted with acute diarrhea in Surabaya, Indonesia: a cross-sectional study<\/a> Fardah Athiyyah A, Shigemura K, Kitagawa K et al.\u00a0<br \/><a target=\"\">Diagnostic value of symptoms and laboratory data for pertussis in adolescent and adult patients<\/a> Miyashita N, Akaike H, Teranishi H, Kawai Y, Ouchi K, Kato T, Hayashi T, Okimoto N.<br \/><a target=\"\">Pertussis (Whooping Cough)<\/a> Centers for Disease Control and Prevention<br \/><a target=\"\">Pertussis prevalence among adult patients with acute cough<\/a> \u0130lbay A, Tanr\u0131\u00f6ver MD, Zarakol P, G\u00fczelce E\u00c7, B\u00f6lek H, \u00dcnal S.\u00a0<br \/><a target=\"\">Clinical aspects of human rabies in the state of Cear\u00e1, Brazil: an overview of 63 cases<\/a> Duarte NFH, Pires Neto RDJ, Viana VF, Feij\u00e3o LX, Alencar CH, Heukelbach J.\u00a0<br \/><a target=\"\">Epidemiological and clinical features of human rabies cases in Bali 2008-2010<\/a> Susilawathi NM, Darwinata AE, Dwija IB, Budayanti NS et al.\u00a0<br \/><a target=\"\">Rubella outbreak among workers in three small- and medium-size business establishments associated with imported genotype 1E rubella virus-Shizuoka, Japan, 2015<\/a> Kato H, Kamiya H, Mori Y, Yahata Y, Morino S, Griffith M et al.\u00a0<br \/><a target=\"\">Rubella (German Measles, Three-Day Measles)<\/a> Centers for Disease Control and Prevention<br \/><a target=\"\">Five years review of cases of adult tetanus managed at Gondar University Hospital, North West Ethiopia (Gondar, Sep. 2003-Aug. 2008)<\/a> Tadesse A, Gebre-Selassie S.\u00a0<br \/><a target=\"\">Clinical features and outcomes of tetanus: a retrospective study<\/a> Fan Z, Zhao Y, Wang S, Zhang F, Zhuang C.\u00a0<br \/><a target=\"\">Tetanos<\/a> Louise Thwaites, MD<br \/><a target=\"\">Tetanus: Presentation and outcome in adults.\u00a0<\/a> Younas NJ, Abro AH, Das K, Abdou AMS, Ustadi AM, Afzal S.\u00a0<br \/><a target=\"\">Miliary tuberculosis: Clinical manifestations, diagnosis and outcome in 38 adults<\/a> Mert, A., Bilir, M., Tabak, F., Ozaras, R., Ozturk, R. et al.\u00a0<br \/><a target=\"\">A Population-Based Survey of Tuberculosis Symptoms: How Atypical Are Atypical Presentations?<\/a> Loren G. Miller, Steven M. Asch, Emily I. Yu, Laura Knowles, Lillian Gelberg, Paul Davidson<br \/><a target=\"\">Alert sign and symptoms for the early diagnosis of pulmonary tuberculosis: analysis of patients followed by a tertiary pediatric hospital<\/a> Farina, E., D\u2019Amore, C., Lancella, L.\u00a0et al.\u00a0<br \/><a target=\"\">Clinical and epidemiological characteristics of HIV\/AIDS patients diagnosed with tuberculosis in the Integral Care Service of the Dr. Robert Reid Cabral Children&#8217;s Hospital during the period 2010-2016<\/a> Ricardo El\u00edas-Melgen, Rosa Abreu, Milandres Garc\u00eda<br \/><a target=\"\">Typhoid FeverAn Epidemic With Remarkably Few Clinical Signs and Symptoms<\/a> Klotz SA,\u00a0Jorgensen JH,\u00a0Buckwold FJ,\u00a0Craven PC.<br \/><a target=\"\">Current trends in typhoid fever<\/a> Crum, N.F.\u00a0<br \/><a target=\"\">Characteristic features of culture positive enteric fever in pediatric teaching hospital in Sulaimani governorate<\/a> Tyib, Tara &amp; Fakhir, Haydar &amp; Mohammad, Hayder<br \/><a target=\"\">Enteric fever<\/a> Basnyat B, Qamar FN, Rupali P, Ahmed T, Parry CM.<br \/><a target=\"\">Clinical Manifestations Of Hepatitis A: Recent Experience In A Community Teaching Hospital<\/a> Myron J. Tong, Neveen S. El-Farra, Marianne I. Grew,<br \/><a target=\"\">Natural History, Clinical Manifestations, and Pathogenesis of Hepatitis A<\/a> Shin EC, Jeong SH<br \/><a target=\"\">Clinical and Epidemiological Spectrum of Acute Viral Hepatitis Due to Hepatitis A and E in Children: A Descriptive, Cross-Sectional, Hospital-Based Study<\/a> Javaria Rasheed,\u00a0Muhammad Khalid, Sobia Rubab,\u00a0Bushra Iqbal, Iram Nawaz,\u00a0Asad Shahzad<br \/><a target=\"\">Assessing yellow Fever risk in the ecuadorian Amazon.\u00a0<\/a> Izurieta RO, Macaluso M, Watts DM, Tesh RB, Guerra B, Cruz LM, Galwankar S, Vermund SH<br \/><a target=\"\">Clinical features of yellow fever cases at Vom Christian Hospital during the 1969 epidemic on the Jos Plateau, Nigeria<\/a> Evan M Jones and D. C. Wilson<br \/><a target=\"\">Clinical and epidemiological characteristics of yellow fever in Brazil: analysis of reported cases 1998-2002<\/a> Tuboi, Suely &amp; Costa, Zouraide &amp; Vasconcelos, Pedro &amp; Hatch, Douglas. <br \/><a target=\"\">An Overview of Yellow Fever Virus Disease<\/a> McGuinness I, Beckham JD, Tyler KL, Pastula DM.<br \/><a target=\"\">Yellow fever outbreak in Kenya: A review<\/a> Olivier Uwishema, Stanley Chinedu Eneh, Anyike Goodness Chiburoma et al.\u00a0<br \/><a target=\"\">Yellow Fever<\/a> Leslie V. Simon;\u00a0Muhammad F. Hashmi;\u00a0Klaus D. Torp.<br \/><a target=\"\">Zika Virus<\/a> The Johns Hopkins University<br \/><a target=\"\">Clinical, laboratory and virological data from suspected ZIKV patients in an endemic arbovirus area<\/a> Tatiana Elias Colombo, C\u00e1ssia Fernanda Estofolete, Andr\u00e9ia Francesli Negri Reis et al.\u00a0<br \/><a target=\"\">Clinical relevance of Zika symptoms in the context of a Zika Dengue epidemic<\/a> Humberto Guanche Garcell, Francisco Guti\u00e9rrez Garc\u00eda, Manuel Ramirez Nodal et al.\u00a0<br \/><a target=\"\">The Clinical Spectrum of Zika Virus in Returning Travelers<\/a> Eyal Meltzer, Eyal Leshem, Yaniv Lustig, Giora Gottesman, Eli Schwartz<\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96a2c59 elementor-widget elementor-widget-text-editor\" data-id=\"96a2c59\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Cada enfermedad se describi\u00f3 a partir de varios signos agrupados en ocho categor\u00edas espec\u00edficas. Se llevaron a cabo entrevistas espec\u00edficas con expertos m\u00e9dicos para determinar los elementos cruciales en el diagn\u00f3stico de enfermedades infecciosas y su relaci\u00f3n con los par\u00e1metros de toma de decisiones cl\u00ednicas. Hemos desarrollado una tabla que representa las frecuencias de los diversos s\u00edntomas de enfermedades. Cada fila de la tabla corresponde a una enfermedad espec\u00edfica y cada columna corresponde a un s\u00edntoma particular. La intersecci\u00f3n de una fila y una columna contiene la frecuencia o la aparici\u00f3n de un s\u00edntoma espec\u00edfico para una enfermedad en particular.<\/p><table><tbody><tr><td colspan=\"4\"><p style=\"text-align: center;\">Grupos de signos de enfermedades infecciosas<\/p><\/td><\/tr><tr><td><p>General\/signos sist\u00e9micos<\/p><\/td><td><ul><li>Fiebre continua o fiebre con intervalos de menos de un d\u00eda<\/li><li>Fiebre intermitente cada 2-4 d\u00edas<\/li><li>Letargo<\/li><li>sudoraci\u00f3n y\/o escalofr\u00edos<\/li><li>Dolor de cabeza<\/li><li>Falta de apetito y\/o p\u00e9rdida de peso<\/li><\/ul><\/td><td><p>S\u00edntomas hematol\u00f3gicos<\/p><\/td><td><ul><li>manifestaciones hemorr\u00e1gicas<\/li><\/ul><\/td><\/tr><tr><td><p>Signos respiratorios\u00a0<\/p><\/td><td><ul><li>Dolor de pecho<\/li><li>Tos<\/li><li>Flema<\/li><li>dificultad para respirar<\/li><li>Dolor de garganta<\/li><li>rinorrea<\/li><\/ul><\/td><td><p>S\u00edntomas g\u00e1stricos<\/p><\/td><td><ul><li>abdominal pain<\/li><li>diarrea<\/li><li>nausea<\/li><li>v\u00f3mitos<\/li><\/ul><\/td><\/tr><tr><td><p>3. Signos musculoesquel\u00e9ticos<\/p><\/td><td><ul><li>Dolor de espalda<\/li><li>Dolor en las articulaciones<\/li><li>Dolor muscular<\/li><li>trismo<\/li><\/ul><\/td><td><p>7. Signos dermatol\u00f3gicos o asociados:<\/p><p>\u00a0<\/p><\/td><td><ul><li>hinchaz\u00f3n del cuello<\/li><li>erupci\u00f3n cut\u00e1nea<\/li><li>piel amarilla y\/o orina oscura<\/li><\/ul><\/td><\/tr><tr><td><p>Signos neurol\u00f3gicos<\/p><\/td><td><ul><li>visi\u00f3n borrosa<\/li><li>dificultades cognitivas<\/li><li>dificultad para tragar<\/li><li>mareo<\/li><li>agitaci\u00f3n emocional<\/li><li>problemas neurol\u00f3gicos con sensaci\u00f3n y movimiento<\/li><li>convulsiones<\/li><li>Rigidez del cuello y sensibilidad a la luz.<\/li><\/ul><\/td><td><p>Otros signos<\/p><p>\u00a0<\/p><\/td><td><ul><li>miedo al agua<\/li><li>dolor testicular<\/li><li>enrojecimiento de los ojos<\/li><\/ul><\/td><\/tr><\/tbody><\/table><p>\u00a0<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9ac0404 elementor-widget elementor-widget-heading\" data-id=\"9ac0404\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Algoritmo de predicci\u00f3n<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b868649 elementor-widget elementor-widget-text-editor\" data-id=\"b868649\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\tEl objetivo del algoritmo de predicci\u00f3n es proporcionar las posibles enfermedades infecciosas que puede tener un paciente en funci\u00f3n de sus s\u00edntomas. El algoritmo de predicci\u00f3n debe entrenarse, y lo hicimos con la base de conocimientos de s\u00edntomas y enfermedades infecciosas.\n\nLa base de conocimientos de s\u00edntomas y enfermedades infecciosas se expres\u00f3 en porcentajes, es decir, cu\u00e1ntos pacientes de cada 100 manifestar\u00edan un s\u00edntoma espec\u00edfico cuando se infectaran con una enfermedad infecciosa espec\u00edfica. Con base en estos datos, generamos aleatoriamente cientos de pacientes artificiales con s\u00edntomas espec\u00edficos, pero alcanzamos para todos ellos los porcentajes exactos de la base de conocimientos. Por ejemplo, si para una enfermedad espec\u00edfica el 25% de los pacientes tienen el s\u00edntoma 1, el 50% de ellos el s\u00edntoma 2 y el 100% de ellos el s\u00edntoma 3, podr\u00edamos generar los siguientes 5 pacientes a partir de estos datos y los porcentajes generales seguir\u00edan coincidiendo con los datos iniciales. Utilizamos este enfoque de generaci\u00f3n aleatoria de pacientes artificiales para tener en cuenta que cada ser humano es \u00fanico, por lo que los s\u00edntomas que aparecen despu\u00e9s de la infecci\u00f3n son ligeramente diferentes para cada persona.\n<table>\n<tbody>\n<tr>\n<td>Paciente<\/td>\n<td>S\u00edntoma 1<\/td>\n<td>S\u00edntoma 2<\/td>\n<td>S\u00edntoma 3<\/td>\n<\/tr>\n<tr>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td>1<\/td>\n<td><\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td><\/td>\n<td>1<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>4<\/td>\n<td><\/td>\n<td><\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>5<\/td>\n<td><\/td>\n<td>1<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>6<\/td>\n<td><\/td>\n<td><\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>7<\/td>\n<td><\/td>\n<td>1<\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td>8<\/td>\n<td><\/td>\n<td><\/td>\n<td>1<\/td>\n<\/tr>\n<tr>\n<td><\/td>\n<td>25%<\/td>\n<td>50%<\/td>\n<td>100%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\nUsamos estos datos generados aleatoriamente para entrenar nuestro algoritmo de predicci\u00f3n. En nuestro algoritmo de predicci\u00f3n, probamos tres modelos de IA para poder compararlos y seleccionar el m\u00e1s preciso: bosque aleatorio, \u00e1rbol de decisiones y Bayes ingenuo. Todos estos modelos se utilizan para predecir una enfermedad directamente en funci\u00f3n de los s\u00edntomas dados.\n\n1. El modelo Bayes ingenuo es un clasificador que supone que los s\u00edntomas son condicionalmente independientes, dada la enfermedad objetivo. La solidez de esta suposici\u00f3n (ingenuidad) es lo que le da el nombre al clasificador.\n\n2. El modelo de \u00e1rbol de decisiones es un modelo en forma de \u00e1rbol de s\u00edntomas y sus posibles enfermedades, que incluye resultados de eventos aleatorios, costos de recursos y utilidad. Cada rama representa el resultado de la prueba (si un s\u00edntoma est\u00e1 presente o no) y cada nodo de hoja representa una enfermedad. En la siguiente imagen se muestra un \u00e1rbol de decisiones completo.\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bf662c6 elementor-widget elementor-widget-image\" data-id=\"bf662c6\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.10.1 - 17-01-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/dessevproject.eu\/wp-content\/uploads\/2024\/04\/decision-tree.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"decision tree\" e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6MjA3NywidXJsIjoiaHR0cHM6XC9cL2Rlc3NldnByb2plY3QuZXVcL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjRcLzA0XC9kZWNpc2lvbi10cmVlLnBuZyJ9\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/dessevproject.eu\/wp-content\/uploads\/elementor\/thumbs\/decision-tree-qn7xzc84w17o7jdimskjs82u9b296ta9ydjpsruku8.png\" title=\"decision tree\" alt=\"decision tree\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f79f1fe elementor-widget elementor-widget-text-editor\" data-id=\"f79f1fe\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>3. El modelo de bosque aleatorio se basa en el modelo de \u00e1rbol de decisi\u00f3n, pero en este \u00faltimo se genera un bosque (una gran cantidad) de \u00e1rboles de decisi\u00f3n considerando solo algunos s\u00edntomas para cada \u00e1rbol de decisi\u00f3n. El resultado del bosque aleatorio es la enfermedad seleccionada por la mayor\u00eda de los \u00e1rboles de decisi\u00f3n.<\/p>\n<p>Se utiliz\u00f3 el software de miner\u00eda de datos Orange para construir los tres modelos.\u00a0<span style=\"font-style: inherit; font-weight: inherit; background-color: var(--ast-global-color-4); color: var(--ast-global-color-3);\">El software de miner\u00eda de datos Orange es uno de los programas para el aprendizaje autom\u00e1tico y la miner\u00eda de datos. Lo usamos porque es un software gratuito y ampliamente utilizado desde el cual los modelos generados se pueden exportar y luego usar en casi cualquier lugar mediante una biblioteca de Python de Orange (Demsar J, Curk T, Erjavec A, Gorup C, Hocevar T, Milutinovic M, Mozina M, Polajnar M, Toplak M, Staric A, Stajdohar M, Umek L, Zagar L, Zbontar J, Zitnik M, Zupan B (2013) Orange: Data Mining Toolbox in Python, Journal of Machine Learning Research 14 (agosto): 2349\u22122353. http:\/\/jmlr.org\/papers\/volume14\/demsar13a\/demsar13a.pdf). Esto nos permite integrar f\u00e1cilmente el algoritmo de predicci\u00f3n en el sitio web y la aplicaci\u00f3n m\u00f3vil y ponerlo a disposici\u00f3n del p\u00fablico.<\/span><\/p>\n<p><span style=\"font-style: inherit; font-weight: inherit; background-color: var(--ast-global-color-4); color: var(--ast-global-color-3);\">En la siguiente imagen se muestra la visualizaci\u00f3n del proyecto en el software de miner\u00eda de datos Orange.<\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b39cbfc elementor-widget elementor-widget-image\" data-id=\"b39cbfc\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/dessevproject.eu\/wp-content\/uploads\/2024\/04\/orange.png\" data-elementor-open-lightbox=\"yes\" data-elementor-lightbox-title=\"orange\" e-action-hash=\"#elementor-action%3Aaction%3Dlightbox%26settings%3DeyJpZCI6MjA5OSwidXJsIjoiaHR0cHM6XC9cL2Rlc3NldnByb2plY3QuZXVcL3dwLWNvbnRlbnRcL3VwbG9hZHNcLzIwMjRcLzA0XC9vcmFuZ2UucG5nIn0%3D\">\n\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/dessevproject.eu\/wp-content\/uploads\/elementor\/thumbs\/orange-qn7yrjb5z3mgtt8txb1637r1a9dbccsxxyuv7lrgis.png\" title=\"orange\" alt=\"orange\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f3c4b2c elementor-widget elementor-widget-heading\" data-id=\"f3c4b2c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Evaluaci\u00f3n de resultados<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-43c6d06 elementor-widget elementor-widget-text-editor\" data-id=\"43c6d06\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span lang=\"EN-GB\">Esta<\/span><span lang=\"EN-GB\"> En esta secci\u00f3n se presenta la evaluaci\u00f3n de tres modelos de aprendizaje autom\u00e1tico diferentes: Random Forest, Naive Bayes y Decision Tree. Los modelos se evaluaron utilizando varias m\u00e9tricas de rendimiento para determinar su idoneidad para la implementaci\u00f3n.<\/span><\/p>\n<p><span lang=\"EN-GB\"><br><span style=\"color: var(--ast-global-color-2); font-family: Poppins, sans-serif; font-size: 1rem; font-style: inherit; font-weight: 600; background-color: var(--ast-global-color-4);\">Conjunto de datos utilizado<\/span><br><\/span><\/p>\n<p><span lang=\"EN-GB\">Recopilamos una peque\u00f1a cantidad de s\u00edntomas y combinaciones de enfermedades de pacientes reales como datos de prueba. Cabe destacar que los datos de prueba no se utilizaron durante el proceso de entrenamiento al construir estos modelos.<\/span><\/p>\n<p><span lang=\"EN-GB\"><br><span style=\"color: var(--ast-global-color-2); font-family: Poppins, sans-serif; font-size: 1rem; font-style: inherit; font-weight: 600; background-color: var(--ast-global-color-4);\">T\u00e9cnicas de validaci\u00f3n<\/span><br><\/span><\/p>\n<p><span lang=\"EN-GB\">El proyecto aplic\u00f3 t\u00e9cnicas de validaci\u00f3n cruzada y muestreo aleatorio para probar la precisi\u00f3n de los modelos. La combinaci\u00f3n de validaci\u00f3n cruzada y muestreo aleatorio facilita una evaluaci\u00f3n integral del desempe\u00f1o de los modelos de aprendizaje autom\u00e1tico. Este enfoque de validaci\u00f3n dual garantiza una comprensi\u00f3n completa de c\u00f3mo funciona el modelo en varios escenarios.<\/span><\/p>\n<p><span lang=\"EN-GB\"><br><span style=\"color: var(--ast-global-color-2); font-family: Poppins, sans-serif; font-size: 1rem; font-style: inherit; font-weight: 600; background-color: var(--ast-global-color-4);\">T\u00e9cnica de validaci\u00f3n cruzada y configuraci\u00f3n de muestreo<\/span><br><\/span><\/p>\n<p><strong>Validaci\u00f3n cruzada<\/strong><\/p>\n<ul type=\"disc\">\n<li><span lang=\"EN-GB\">N\u00famero de pliegues: 5<\/span><\/li>\n<li><span lang=\"EN-GB\">Estratificado: habilitado (garantiza que cada pliegue tenga una distribuci\u00f3n similar de clases)<\/span><\/li>\n<\/ul>\n<p><strong>Muestreo aleatorio<\/strong><\/p>\n<ul type=\"disc\">\n<li><span lang=\"EN-GB\">Repetir entrenamiento\/prueba: 10 veces<\/span><\/li>\n<li><span lang=\"EN-GB\">Tama\u00f1o del conjunto de entrenamiento: 66%<\/span><\/li>\n<li><span lang=\"EN-GB\">Estratificado: habilitado<\/span><\/li>\n<\/ul>\n<h5>Medidas de evaluaci\u00f3n<\/h5>\n<ol start=\"1\" type=\"1\">\n<li><strong>AUC (\u00c1rea bajo la curva)<\/strong><span lang=\"EN-GB\">:Mide la capacidad del modelo para diferenciar entre clases.<\/span><\/li>\n<li><strong>CA (Precisi\u00f3n de clasificaci\u00f3n)<\/strong><span lang=\"EN-GB\">:La relaci\u00f3n entre las instancias predichas correctamente y el total de instancias.<\/span><\/li>\n<li><strong>Puntuaci\u00f3n F1<\/strong><span lang=\"EN-GB\">:La media arm\u00f3nica de precisi\u00f3n y recuperaci\u00f3n.<\/span><\/li>\n<li><strong>Precision<\/strong><span lang=\"EN-GB\">:La relaci\u00f3n entre las observaciones positivas predichas correctamente y el total de observaciones positivas predichas.<\/span><\/li>\n<li><strong>Recordar<\/strong><span lang=\"EN-GB\">:La relaci\u00f3n entre las observaciones positivas predichas correctamente y todas las observaciones de la clase real.<\/span><\/li>\n<li><strong>Coeficiente de correlaci\u00f3n de Matthews (MCC)<\/strong><span lang=\"EN-GB\">:Una medida de la calidad de las clasificaciones binarias.<\/span><\/li>\n<\/ol>\n<h5>Rendimiento del modelo<\/h5>\n<p><span lang=\"EN-GB\">A continuaci\u00f3n se muestra una tabla que resume los resultados de la evaluaci\u00f3n de los tres modelos de aprendizaje autom\u00e1tico: Random Forest, Naive Bayes y Decision Tree.<\/span><\/p>\n<table>\n<tbody>\n<tr>\n<td>M\u00e9trico<\/td>\n<td>Random forest<\/td>\n<td>Naive bayes<\/td>\n<td>Decision tree<\/td>\n<\/tr>\n<tr>\n<td>AUC<\/td>\n<td>1.000<\/td>\n<td>0.998<\/td>\n<td>0.802<\/td>\n<\/tr>\n<tr>\n<td>CA<\/td>\n<td>0.952<\/td>\n<td>0.857<\/td>\n<td>0.571<\/td>\n<\/tr>\n<tr>\n<td>F1<\/td>\n<td>0.937<\/td>\n<td>0.825<\/td>\n<td>0.500<\/td>\n<\/tr>\n<tr>\n<td>Precision<\/td>\n<td>0.929<\/td>\n<td>0.810<\/td>\n<td>0.468<\/td>\n<\/tr>\n<tr>\n<td>Recordar<\/td>\n<td>0.952<\/td>\n<td>0.857<\/td>\n<td>0.571<\/td>\n<\/tr>\n<tr>\n<td>MCC<\/td>\n<td>0.952<\/td>\n<td>0.854<\/td>\n<td>0.559<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><span lang=\"EN-GB\">Esta tabla refleja el desempe\u00f1o de cada modelo en las m\u00e9tricas de evaluaci\u00f3n clave utilizadas en el proyecto DESSEV. La comparaci\u00f3n de los modelos por \u00e1rea bajo la curva ROC indica que el modelo Random Forest es superior, seguido por Naive Bayes, siendo el modelo Decision Tree el menos eficaz.<\/span><\/p><p><span lang=\"EN-GB\"><br><span style=\"font-style: inherit; font-weight: inherit; background-color: var(--ast-global-color-4); color: var(--ast-global-color-3);\">Como el modelo Random Forest tiene el mejor rendimiento, es el modelo utilizado para la predicci\u00f3n de enfermedades en nuestro sitio web y aplicaci\u00f3n m\u00f3vil.<\/span><br><\/span><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Knowledge base Knowledge base in the form of\u201cIF \u2026 THEN \u2026\u201d rules basewhich can be easily implemented into decision support system. Selection of diseases Drawing upon current statistics and data from leading health organisations such as the World Health Organization (WHO, https:\/\/www.cdc.gov\/nndss\/index.html access by day 23 Feb 2024) through its Global Health Observatory (GHO), the &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/dessevproject.eu\/es\/knowledge-base\/\"> <span class=\"screen-reader-text\">Base de conocimientos<\/span> Leer m\u00e1s &raquo;<\/a><\/p>","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"page-builder","ast-global-header-display":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"enabled","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","footnotes":""},"class_list":["post-1943","page","type-page","status-publish","hentry"],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false,"trp-custom-language-flag":false},"uagb_author_info":{"display_name":"admin","author_link":"https:\/\/dessevproject.eu\/es\/author\/admin\/"},"uagb_comment_info":0,"uagb_excerpt":"Knowledge base Knowledge base in the form of\u201cIF \u2026 THEN \u2026\u201d rules basewhich can be easily implemented into decision support system. Selection of diseases Drawing upon current statistics and data from leading health organisations such as the World Health Organization (WHO, https:\/\/www.cdc.gov\/nndss\/index.html access by day 23 Feb 2024) through its Global Health Observatory (GHO), the&hellip;","_links":{"self":[{"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/pages\/1943","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/comments?post=1943"}],"version-history":[{"count":152,"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/pages\/1943\/revisions"}],"predecessor-version":[{"id":2185,"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/pages\/1943\/revisions\/2185"}],"wp:attachment":[{"href":"https:\/\/dessevproject.eu\/es\/wp-json\/wp\/v2\/media?parent=1943"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}