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Integration of AI With ML for Neuropsychological Applications
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Author(s): Prabhjeet Kaur (Lovely Professional University, India), Channi Sachdeva (Lovely Professional University, India), Ravi Kumar Gupta (Maharaja Agrasen Institute of Technology, Delhi, India)and Lokesh Jasrai (Lovely Professional University, India)
Copyright: 2025
Pages: 14
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.ch004
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Abstract
This chapter examines how Artificial Intelligence (AI) and Machine Learning (ML) are being used in neuropsychology, focusing on how they can significantly improve the study and treatment of cognitive issues like Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). Traditional methods in neuropsychology often depend on subjective evaluations, which can reduce the accuracy of diagnoses and delay necessary treatments. AI and ML use large amounts of data to find early signs of cognitive problems and provide better predictive analysis, helping with early detection and more accurate treatment. From a research standpoint, AI offers new tools to examine complex data from brain scans, genetic information, and behaviour tests. Machine learning can identify patterns that suggest how diseases might progress, which could lead to important discoveries in finding markers for diseases and creating treatments tailored to individual patients. The chapter indicates that more research should focus on making AI systems fair and easy to understand and using them in many medical situations.
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