Publication Name	Artificial Intelligence in Medical Imaging
Manuscript ID	117331
Country	Türkiye

Category	Computer Science, Artificial Intelligence
Manuscript Type	Minireviews
Article Title	Artificial intelligence in healthcare: Technical advances, clinical integration, and future perspectives
Manuscript Source	Invited Manuscript
All Author List	Abdulkadir Yıldırım and Öner Özdemir
Funding Agency and Grant Number
Corresponding Author	Öner Özdemir, Department of Pediatric Allergy and Immunology, Faculty of Medical, Sakarya University, Adnan Menderes Cad, Adapazarı 54100, Sakarya, Türkiye. ozdemir_oner@hotmail.com
Key Words	Artificial intelligence; Deep learning; Radiology; Cardiology; Oncology; Clinical decision support; Multimodal imaging; Explainability
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.
Citation	Yıldırım A, Özdemir Ö. Artificial intelligence in healthcare: Technical advances, clinical integration, and future perspectives. Artif Intell Med Imaging 2026; In press

Received	2025-12-05 00:17
Peer-Review Started	2025-12-05 00:18
First Decision by Editorial Office Director	2025-12-16 09:14
Return for Revision	2025-12-16 09:14
Revised	2025-12-26 08:08
Publication Fee Transferred
Second Decision by Editor	2026-01-22 02:33
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-01-22 06:16
Articles in Press	2026-01-22 06:16
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2644-3260 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright	The Author(s) 2026. Published by Baishideng Publishing Group Inc. All rights reserved.
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