STM Journals Peer-reviewed research from Consortium e-Learning Network

Research and Reviews : A Journal of Medical Science and Technology Original Research

Early Disease Detection Using Artificial Intelligence

  1. Pavandeep Kaur Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Mohali
  2. Parul Gogia Department of Computer Science and Engineering, Apex Institute of Technology Chandigarh University Mohali
  3. Aekansh Khandelwal Department of Computer Science and Engineering, Apex Institute of Technology Chandigarh University Mohali
  4. Rishabh Raj Department of Computer Science and Engineering, Apex Institute of Technology Chandigarh University Mohali

Abstract

Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease indicators at their inception, facilitating timely interventions and personalized treatment strategies. Through meticulous data collection, preprocessing, and exploratory analysis, the study establishes the groundwork for the development of robust AI models capable of interpreting complex medical imaging data. The proposed methodology emphasizes the integration of domain- specific clinical expertise to ensure the clinical relevance and interpretability of the models. Rigorous validation and evaluation demonstrate the efficacy and generalization capacity of our approach, paving the way for its seamless integration into clinical practice.

Keywords

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