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Developments, Hardships, and Prospective Directions in the Field of Neuroscience and Neurological Machine Learning for Behavioral Evaluation
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Author(s): Ridhima Sharma (Vivekananda Institute of Professional Studies-TC, India)and Timcy Sachdeva (Vivekananda Institute of Professional Studies-TC, India)
Copyright: 2025
Pages: 16
Source title:
Transforming Neuropsychology and Cognitive Psychology With AI and Machine Learning
Source Author(s)/Editor(s): Rohit Bansal (Stanford Institute of Management and Technology, Australia), Tariq Maqableh (Charles Sturt University, Australia), Gunjan Shuklaa (SICA College, Indore, India), Fazla Rabby (Stanford Institute of Management and Technology, Australia)and Remya Lathabhavan (Indian Institute of Management, Bodh Gaya, India)
DOI: 10.4018/979-8-3693-9341-3.ch018
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Abstract
This study examines the current state of neuroscience, emphasizing the use of machine learning to improve behavioral assessment and its therapeutic applications. Progress in neuroscience has facilitated the comprehension of cognitive aging, neurological illnesses, and the essential function of cognition in detecting cognitive decline. The increasing potential of neurological machine learning likely overcomes the aforementioned deficiencies—consistent monitoring and early identification in mental health—through automation. This research will ultimately address AI-related concerns regarding the longitudinal monitoring of individuals with mental illnesses. Neurocognitive testing may leverage machine learning to significantly advance the evaluation and early management of cognitive health, hence facilitating future research to enhance and broaden the capabilities of neurolearning and cognitive neuropsychology.
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