December 2025
Intermediate to advanced
544 pages
14h 4m
English
Content preview from Brain Informatics Technology
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16Mental Health Detection and Prediction through Machine Learning Technology: Issues and Future Opportunities
Kedar Nath Singh1*, Harsh Pratap Singh2, Mahesh Panjwani3 and Snehil Dahima4
1Department of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India
2Department of Computer Science and Engineering, Medicaps University, Indore, Madhya Pradesh, India
3Department of Computer Science and Engineering, Priyadarshini College of Engineering, Nagpur, Maharashtra, India
4Department of Computer Application, SIES College of Management Studies, Mumbai University, Maharashtra, India
Abstract
Through the analysis of mental health data, machine learning approaches are enhancing the diagnosis, treatment, and comprehension of a variety of medical conditions, addressing particular problems and possible solutions. Brain conditions including dementia, migraine, depression, and cerebrovascular illness are the main causes of international impairment. The biomedical sciences are incorporating machine learning to improve the sensitivity, specificity, and impartiality of clinical decision-making, monitoring, and illness diagnosis. In order to diagnose diseases like Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, epilepsy, stroke, migraine, peripheral neuropathy, traumatic brain injury, Huntington’s disease, amyotrophic lateral sclerosis, and others, machine learning techniques are being used to speed up decision-making, reduce false positive rates, ...
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