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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
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© Medicine and Pharmacy Reports, 2024
Affiliations
Stefan Lucian Popa
2nd Department of Internal Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania
Abdulrahman Ismaiel
2nd Department of Internal Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania
Vlad Dumitru Brata
2. Faculty of Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania
Daria Claudia Turtoi
2. Faculty of Medicine, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania
Maria Barsan
3. Department of Occupational Health, "Iuliu Hatieganu" University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania
Zoltan Czako
4. Department of Computer Science, Technical University of Cluj-Napoca, 400027 Cluj-Napoca, Romania
Cristina Pop
5. Department of Pharmacology, Physiology and Pathophysiology, Faculty of Pharmacy, "Iuliu Hațieganu" University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania
Lucian Muresan
6. Department of Cardiology,” Emile Muller” Hospital, Mulhouse, 68200 Mulhouse, France
Mihaela Fadgyas Stanculete
7. Department of Neurosciences, Discipline of Psychiatry and Pediatric Psychiatry, Iuliu Hatieganu University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania
Dinu Iuliu Dumitrascu
8. Department of Anatomy, "Iuliu Hatieganu" University of Medicine and Pharmacy Cluj-Napoca, 400000 Cluj-Napoca, Romania
How to Cite
Artificial Intelligence and medical specialties: support or substitution?
Abstract
The rapid advancement of artificial intelligence (AI) in healthcare has spurred extensive debate regarding its potential to replace human expertise across various medical specialties. This narrative review critically examines the integration of AI within diverse medical specialties to discern its role as a substitute or supporter. The analysis encompasses AI’s impact on diagnostic precision, treatment planning, and patient care. Although AI systems have demonstrated remarkable proficiency in tasks reliant on data analysis and pattern recognition, they fall short in areas necessitating nuanced decision-making, empathetic communication, and the application of human medical expertise in diagnosis and treatment planning. The rapid evolution of AI applications within medical specialties is propelled by the swift advancements in both hardware and software technologies, fostering a dynamic synergy that continues to redefine the boundaries of precision and efficiency in healthcare delivery. While AI demonstrates remarkable capabilities in automating tasks, it is underscored that its integration in complex domains necessitates a balanced approach that preserves the indispensable contributions of human activity.