Journal of Artificial Intelligence, Machine Learning and Soft Computing

Abstract

Artificial Intelligence (AI) has emerged as a transformative technology in healthcare, particularly in diagnosis and prognostics. AI-powered systems can analyze complex medical datasets, identify patterns in patient data, and predict disease outcomes with high accuracy. This review explores AI methodologies applied in healthcare, including machine learning (ML), deep learning (DL), natural language processing (NLP), and hybrid approaches. The paper highlights AI applications in radiology, pathology, genomics, and clinical decision support systems. Furthermore, challenges such as data privacy, algorithmic bias, interpretability, and clinical integration are discussed. Finally, future directions are outlined, emphasizing AI’s role in personalized medicine and predictive healthcare.

Keywords: Artificial Intelligence, Healthcare, Diagnosis, Prognostics, Machine Learning, Deep Learning, Predictive Analytics, Clinical Decision Support