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Artif Intell Med Imaging. Sep 8, 2026; 7(1): 117331
Published online Sep 8, 2026. doi: 10.35711/aimi.v7.i1.117331
Published online Sep 8, 2026. doi: 10.35711/aimi.v7.i1.117331
Artificial intelligence in healthcare: Technical advances, clinical integration, and future perspectives
Abdulkadir Yıldırım, Medical Faculty, Sakarya University, Adapazarı 54100, Türkiye
Öner Özdemir, Department of Pediatric Allergy and Immunology, Faculty of Medicine, Sakarya University, Research and Training Hospital, Adapazarı 54100, Türkiye
Author contributions: Yıldırım A and Özdemir Ö contributed to manuscript preparation, all aspects of this manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Öner Özdemir, MD, Department of Pediatric Allergy and Immunology, Faculty of Medicine, Sakarya University, Research and Training Hospital, Adnan Menderes Cad, Adapazarı 54100, Türkiye. ozdemir_oner@hotmail.com
Received: December 5, 2025
Revised: December 26, 2025
Accepted: January 22, 2026
Published online: September 8, 2026
Processing time: 270 Days and 22.6 Hours
Revised: December 26, 2025
Accepted: January 22, 2026
Published online: September 8, 2026
Processing time: 270 Days and 22.6 Hours
Core Tip
Core Tip: Artificial intelligence (AI) is undergoing a paradigm shift from task-specific convolutional architectures to multimodal foundation models. While AI has demonstrated diagnostic performance comparable to experts in radiology, cardiology, and oncology-particularly in retrospective imaging cohorts-its seamless clinical integration remains contingent on overcoming barriers related to explainability, data privacy, and the transition from retrospective validation to prospective clinical trials. This review synthesizes current technical milestones and critically evaluates the path toward implementing human-centric AI.