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Publication Information
Affiliation
Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.; Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.; Department of Electrical Engineering, Qatar University, Doha 2713, Qatar.; Department of Electrical Engineering, Qatar University, Doha 2713, Qatar.; Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.; Neuromuscular Division, Hamad General Hospital, Doha 3050, Qatar.; Department of Neurology, BIRDEM General Hospital, Dhaka-1000, Bangladesh.; Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.; Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.; Department of Physics and Electronics, Dr. Ram Manohar Lohia Avadh University, Ayodhya 224001, India.
Authors
Haque Fahmida, Reaz Mamun B I, Chowdhury Muhammad E H, Kiranyaz Serkan, Ali Sawal H M, Alhatou Mohammed, Habib Rumana, Bakar Ahmad A A, Arsad Norhana, Srivastava Geetika
Studies
Abstract
Diabetic sensorimotor polyneuropathy (DSPN) is a major form of complication that arises in long-term diabetic patients. Even though the application of machine learning (ML) in disease diagnosis is very common and well-established in the field of research, its application in DSPN diagnosis using nerve conduction studies (NCS), is very limited in the existing literature.