Sowmiyalakshmi Ganesh
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Sowmiyalakshmi Ganesh has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Jayakumar Kaliappan
Vellore Institute of Technology
1 shared publication - Kathiravan Srinivasan
School of Computer Science and Engineering, Vellore Institute of Technology
1 shared publication - Nadesh Ramu Krishnan
School of Computer Science Engineering and Information Systems, Vellore Institute of Technology
1 shared publication - P. M. Durai Raj Vincent
School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India
1 shared publication - Thillai Chithambaram
School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
1 shared publication
Latest Publications
- Open Access
- 3 December 2023
- Published by MDPI AG in Diagnostics
- Vol. 13 (23) , 3592
Exploring Huntington’s Disease Diagnosis via Artificial Intelligence Models: A Comprehensive Review
Huntington’s Disease (HD) is a devastating neurodegenerative disorder characterized by progressive motor dysfunction, cognitive impairment, and psychiatric symptoms. The early and accurate diagnosis of HD is crucial for effective intervention and patient care. This comprehensive review provides a comprehensive overview of the utilization of Artificial Intelligence (AI) powered algorithms in the diagnosis of HD. This review systematically analyses the existing literature to identify key trends, methodologies, and challenges in this emerging field. It also highlights the potential of ML and DL approaches in automating HD diagnosis through the analysis of clinical, genetic, and neuroimaging data. This review also discusses the limitations and ethical considerations associated with these models and suggests future research directions aimed at improving the early detection and management of Huntington’s disease. It also serves as a valuable resource for researchers, clinicians, and healthcare professionals interested in the intersection of machine learning and neurodegenerative disease diagnosis.
- 3 December 2023
- Published by MDPI AG in Diagnostics
- Vol. 13 (23) , 3592
Open AccessExploring Huntington’s Disease Diagnosis via Artificial Intelligence Models: A Comprehensive Review
Huntington’s Disease (HD) is a devastating neurodegenerative disorder characterized by progressive motor dysfunction, cognitive impairment, and psychiatric symptoms. The early and accurate diagnosis of HD is crucial for effective intervention and patient care. This comprehensive review provides a comprehensive overview of the utilization of Artificial Intelligence (AI) powered algorithms in the diagnosis of HD. This review systematically analyses the existing literature to identify key trends, methodologies, and challenges in this emerging field. It also highlights the potential of ML and DL approaches in automating HD diagnosis through the analysis of clinical, genetic, and neuroimaging data. This review also discusses the limitations and ethical considerations associated with these models and suggests future research directions aimed at improving the early detection and management of Huntington’s disease. It also serves as a valuable resource for researchers, clinicians, and healthcare professionals interested in the intersection of machine learning and neurodegenerative disease diagnosis.