Patricia Hafner, Simone Schmidt, Sabine Schädelin, Pascal Rippert, Dalil Hamroun, Solenn Fabien, Bettina Henzi, Niveditha Putananickal, Daniela Rubino-Nacht, Carole Vuillerot, Dirk Fischer
Implementation of Motor Function Measure score percentile curves - Predicting motor function loss in Duchenne muscular dystrophy
European journal of paediatric neurology : EJPN : official journal of the European Paediatric Neurology Society
detect marchiafava bignami disease mbd using distinct deep learning technique advanced deep learning methods becoming crucial contemporary medical diagnostics particularly detecting intricate uncommon neurological illnesses mbd rare neurodegenerative disorder sometimes associated persistent alcoholism characterized loss myelin tissue death corpus callosum poses significant diagnostic difficulties owing infrequency subtle signs exhibits first stages clinically radiological scans novel method variational autoencoders vaes conjunction attention mechanisms used identify mbd peculiar diseases accurately vaes wellknown proficiency unsupervised learning anomaly detection excel analyzing extensive brain imaging datasets uncover subtle patterns abnormalities traditional diagnostic approaches may overlook especially related specific diseases use attention mechanisms enhances technique enabling model concentrate crucial elements imaging data similar discerning observation skilled radiologist thus utilized vae attention mechanisms study detect mbd combination enables prompt identification mbd assists formulating customized efficient treatment strategies significant breakthrough field creation vae equipped attention mechanisms shown outstanding performance achieving accuracy rates 90 accurately differentiating mbd neurodegenerative disorders model underwent training using diverse range mri images shown notable level sensitivity specificity significantly minimizing frequency false positive results strengthening confidence dependability sophisticated automated diagnostic tools