AI in Neurodegeneration Prediction

Author:

Nutulapati Neelima Priyanka1,Karunakaran Naresh Babu2,Banupriya V.3,Sivasundaram Malatthi4,Kaveripakam Venkata Ramana5

Affiliation:

1. SRK Institute of Technology, India

2. Sree Abirami College of Occupational Therapy, India

3. M. Kumarasamy College of Engineering, India

4. K.S.R. College of Engineering, India

5. Sri Vasavi Engineering College, India

Abstract

This chapter explores the capability of artificial intelligence (AI) in predicting the development of neurodegenerative sicknesses, in particular focusing on Alzheimer's ailment. The goal is to recognize the cutting-edge nation of AI studies in this area and identify rising superior procedures. Through conducting a complete literature evaluation and reading existing research, the authors spotlight the strengths and barriers of the use of AI for neurodegeneration prediction. Similarly, they discuss the role of huge information, system mastering, and deep mastering strategies in developing accurate and reliable prediction models. These findings endorse that AI has the capacity to seriously enhance early diagnosis and prediction of Alzheimer's disease progression. We conclude with ability future instructions and demanding situations in this unexpectedly increasing studies vicinity

Publisher

IGI Global

Reference27 articles.

1. Review of Crime Prediction Through Machine Learning.;A. A.Alsubayhin;International Journal of Intelligent Systems and Applications in Engineering,2024

2. A survey of the recent trends in deep learning for literature based discovery in the biomedical domain

3. Advancing Neurodegenerative Disorder Diagnosis: A Machine Learning-Driven Evaluation of Assessment Modalities.;S.Charade;International Journal of Intelligent Systems and Applications in Engineering,2024

4. Longitudinal Assessment of Alzheimer’s Disease Progression Through Structural MRI Analysis and Firefly Algorithm-Based Biomarker Identification.;P.Ediga;International Journal of Intelligent Systems and Applications in Engineering,2024

5. Interpretable deep learning model for major depressive disorder assessment based on functional near-infrared spectroscopy

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3