Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/136075
Title: MACHINE LEARNING BASED CLINICAL DECISION SUPPORT SYSTEM FOR DIAGNOSIS OF NEURODEGENERATIVE DISEASES (MCADS-ND)
Authors: GURPREET SINGH
Keywords: Neurodegenerative Disease Diagnosis, Parkinson Disease, Alzheimer Disease, Self-Organizing Maps, Clinical Decision Support System, Machine Learning
Issue Date: 22-Dec-2014
Source: GURPREET SINGH (2014-12-22). MACHINE LEARNING BASED CLINICAL DECISION SUPPORT SYSTEM FOR DIAGNOSIS OF NEURODEGENERATIVE DISEASES (MCADS-ND). ScholarBank@NUS Repository.
Abstract: Neuroimaging research is an interdisciplinary field that is impacting neuroscience, psychiatry, neurology, and other related disciplines. Despite the recent advancements in neuroimaging, medical diagnosis is still mainly based on a manual assessment of patient’s history and valuation of his/her observable signs and symptoms. Thus, the onus of confirmative diagnosis heavily relies only on the expertise of a physician. We have developed a battery of machine learning based systems to aid clinicians in differential disease diagnosis. The applied methodologies successfully achieved high prediction accuracy especially on images obtained from early-stages of the disease. In clinical settings, the induction of these algorithms as a decision support system could make a significant impact on treatment strategies especially by aiding early disease diagnosis.
URI: http://scholarbank.nus.edu.sg/handle/10635/136075
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