biostudies-literatureUnknown4(10)Lam JY<h4>Background</h4>Multisystem inflammatory syndrome in children (MIS-C) is a novel disease that was identified during the COVID-19 pandemic and is characterised by systemic inflammation following SARS-CoV-2 infection. Early detection of MIS-C is a challenge given its clinical similarities to Kawasaki disease and other acute febrile childhood illnesses. We aimed to develop and validate an artificial intelligence algorithm that can distinguish among MIS-C, Kawasaki disease, and other similar febrile illnesses and aid in the diagnosis of patients in the emergency department and acute care setting.<h4>Methods</h4>In this retrospective model development and validation study, we developed a deep-learning algorithm called KIDMATCH (Kawasaki Disease vs Multisystem Inflammatory Syndrome in ChildreThe Lancet. Digital healthe717-e726https://www.ebi.ac.uk/biostudies/studies/S-EPMC9507344biostudies-literatureA machine-learning algorithm for diagnosis of multisystem inflammatory syndrome in children and Kawasaki disease in the USA: a retrospective model development and validation study.PMC9507344Cohen HJManaloor JJScalici PKumar MRosenkranz MHao SD'Addese LGutglass DJBainto EVayngortin TGardiner MAHite MNguyen MBRometo AHogan AHMelish MAbe NSykes MDionne ADonofrio-Odmann JJSivilay NSalazar JCDeBiasi RLSzmuszkovicz JRRowley AHMohandas SBryl AWLam JYTremoulet AHEkpenyong AShimizu CBocchini JCHARMS Study GroupAng JYBurns JCHarahsheh ASRoberts SCKanegaye JTUlrich SNatale JESchwartz KPediatric Emergency Medicine Kawasaki Disease Research GroupAustin-Page LRNemati SJone PNAnderson MSamuy NZimmerman ELing XBMahanta SAnsusinha EDominguez SGutierrez MPAshouri NNewburger JWMorgan LfalseA machine-learning algorithm for diagnosis of multisystem inflammatory syndrome in children and Kawasaki disease in the USA: a retrospective model development and validation study.<h4>Background</h4>Multisystem inflammatory syndrome in children (MIS-C) is a novel disease that was identified during the COVID-19 pandemic and is characterised by systemic inflammation following SARS-CoV-2 infection. Early detection of MIS-C is a challenge given its clinical similarities to Kawasaki disease and other acute febrile childhood illnesses. We aimed to develop and validate an artificial intelligence algorithm that can distinguish among MIS-C, Kawasaki disease, and other similar febrile illnesses and aid in the diagnosis of patients in the emergency department and acute care setting.<h4>Methods</h4>In this retrospective model development and validation study, we developed a deep-learning algorithm called KIDMATCH (Kawasaki Disease vs Multisystem Inflammatory Syndrome in Childre2022-01-01T00:00:00Z2022 Oct2025-04-21T20:06:39.955Z2024-12-03T23:42:50.875ZS-EPMC95073443615078110.1016/S2589-7500(22)00149-2