1Assistant Professor, Department of CSBS, KGiSL Institute of Technology, India. Orc id: 0009-0002-6324-729X. Email: jayapratibhar7106@gmail.com
2Assistant Professor / MBA, Dr N.G.P Institute of Technology, Coimbatore, India. Email: nsnithya1997@gmail.com
3Assistant Professor, Department of Artificial intelligence and Data Science, Nehru Institute of Engineering and Technology, Coimbatore, India. Email: nietkalpanagcse@nehrucolleges.com
4Associate Professor, Department of Artificial Intelligence and Data Science, Rathinam Technical Campus, Coimbatore, India. Email: cpthamil.selvi72@gmail.com
5Assistant Professor, Department of Computer Science and Design, Erode Sengunthar Engineering College, Perundurai, India. Email: angelannaprathibaecs@esec.ac.in
6Professor, Department of CSE, VSB College of Engineering Technical Campus, Coimbatore, India. Email: tkalaikumaran@gmail.com
The integration of artificial intelligence (AI) in healthcare diagnostics has revolutionized the early detection of diseases and personalisation of treatment. This study aims to understand the contribution of AI-based diagnostic systems to help find early detection of diseases such as cancer, heart disease and brain disorder. In addition, the document discusses how AI creates personalised treatment plans. In other words, the interventions may be chosen individually since the plans use the patient's own data. The challenges associated with data privacy, algorithmic bias, and integration of systems will be interconnected. Machine learning, data and analytics program, and medical imaging AI applications will be examined in the systematic review. The primary findings disclose that the accuracy of diagnosis, lowered costs of healthcare, more effective and personalised one-on-one care. Nonetheless, there are barriers to the implementation of such systems, such as regulatory constraints and the need for large high-quality datasets. In the end section, the paper notes future possibilities of AI for healthcare and how we can overcome challenges in the future to increase the adoption of AI for health.
Keywords: AI-Driven Diagnostics, Early Disease Detection, Personalized Treatment, Healthcare AI, Machine Learning in Healthcare, Medical Imaging, Predictive Analytics.
How to cite this article: Chandran JPR, Nithya NS, Kalpana G, Selvi CPT, Prathiba EAA, Kalaikumaran T. Revolutionizing Healthcare: The Role of AI-Driven Diagnostic Systems in Early Disease Detection and Personalized Treatment. Int J Drug Deliv Technol. 2026;16(19s): 35-39. DOI: 10.25258/ijddt.16.19s.5
Source of support: Nil.
Conflict of interest: None