The Role of Artificial Intelligence in Early Disease Detection Techniques, Applications, Challenges and Future Directions

Ciona Dewan, Raghu Raja Mehra

Abstract: Early and accurate detection of disease is one of the most decisive factors in patient survival, treatment cost and quality of life. Artificial intelligence (AI), and in particular machine learning and deep learning, has emerged as a powerful ally in this effort, capable of analysing medical images, electronic health records, laboratory results and wearable-sensor data with remarkable speed and consistency. This paper reviews the role of AI in early disease detection, surveying the principal techniques, the typical detection pipeline, and applications across cancer, cardiovascular, ophthalmic and neurological disorders. A comparison with conventional diagnostic methods shows that AI systems can match or exceed clinician-level accuracy in several screening tasks while operating at scale. The paper then proposes an integrated, privacy-preserving and explainable framework for clinical deployment, and critically examines the advantages, limitations, and ethical and regulatory challenges involved. Finally, it outlines future directions-including federated learning, explainable AI and continuous wearable monitoring-that could make trustworthy, equitable early detection a routine part of care.

Keywords: artificial intelligence, machine learning, deep learning, early disease detection, medical imaging, screening, explainable AI, healthcare

How to Cite?: Ciona Dewan, Raghu Raja Mehra, "The Role of Artificial Intelligence in Early Disease Detection Techniques, Applications, Challenges and Future Directions", Volume 15 Issue 6, June 2026, International Journal of Science and Research (IJSR), Pages: 1134-1137, https://www.ijsr.net/getabstract.php?paperid=SR26620171630, DOI: https://dx.doi.org/10.21275/SR26620171630

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