Neurodegenerative disease detection and severity prediction using deep learning approaches

Erdas, Cagatay BerkeSumer, EmreKibaroglu, Seda2022-08-112022-08-1120211746-8094http://hdl.handle.net/11727/7321Neurodegenerative diseases (NDDs) such as amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and Parkinson's disease (PD) can manifest themselves anatomically by degeneration in the brain as well as motor symptoms. The motor symptoms can affect walking dynamics in a disease-specific fashion; characteristically they disrupt gait. As the severity of the disease increases, walking ability deteriorates. We examined the effect of NDDs such as ALS, HD, and PD on gait and developed a convolutional long short-term memory (ConvLSTM) and threedimensional convolutional learning network (3D CNN)-based approach to detecting neurodegenerative conditions and predicting disease severity.enginfo:eu-repo/semantics/closedAccessNeurodegenerative diseaseClassification of NDDPrediction of NDDConvLSTM3D CNNNeurodegenerative disease detection and severity prediction using deep learning approachesarticle700006977730000032-s2.0-85112816613