V2I8P4

AI-Powered Early Disease Detection and Image Analysis in Modern Healthcare

Nitesh Vashishtha^1*, Nitin Goel²

Abstract

Artificial Intelligence (AI) holds significant potential for improving patient care and advancing intelligent healthcare systems. In the medical field, AI techniques- particularly machine learning and deep learning- are widely used for drug discovery, risk assessment, and disease diagnosis. Reliable diagnosis using AI requires access to diverse medical data sources, such as genomic data, CT scans, ultrasounds, MRIs, and mammograms. AI also enhances hospital management by reducing patient recovery time and expediting discharge processes. This article explores the application of AI in diagnosing diseases such as stroke, heart conditions, cancer, tuberculosis, and hypertension. A comprehensive survey was conducted using medical imaging datasets, focusing on feature extraction and prediction methods. Studies published up to October 2020 were selected based on their use of AI for early disease detection. The review follows systematic review and meta-analysis guidelines, evaluating performance using metrics such as accuracy, sensitivity, specificity, AUC, precision, recall, and F1-score.

Keywords:

Artificial intelligence, Alzheimer’s disease, cancer, heart disease, chronic illness, and tuberculosis