Published Paper Details:

Artificial intelligence (AI) is increasingly influencing modern healthcare by enhancing disease diagnosis and supporting the advancement of personalized medicine. This review discusses the application of AI-based technologies, particularly machine learning and deep learning, in the analysis of complex medical data such as clinical records, medical imaging, and genomic information. These approaches improve diagnostic precision, facilitate early disease detection, and assist healthcare professionals in making timely and accurate clinical decisions. AI-driven techniques have demonstrated notable success in cancer diagnosis, especially in skin cancer, through automated image processing and pattern recognition methods. Furthermore, AI-enabled personalized medicine allows treatment strategies to be customized according to individual genetic profiles, biomarkers, lifestyle factors, and disease characteristics, thereby reducing unnecessary interventions and treatment-related adverse effects. Although challenges related to data quality, ethical concerns, and clinical implementation persist, ongoing research and technological progress are expected to overcome these limitations. Overall, AI has strong potential to reshape healthcare by enabling more accurate diagnosis and patient-specific therapeutic approaches.