Year: 2026
Type: article
Abstract: A r t i f i c i a l i nt e l l i g e n c e (AI) is no longer a distant or experimental concept in medicine.From radiology and pathology to research writing and clinical documentation, AI-based systems are already e mb e d d e d i nto e ve r yd ay medical practice [1].Yet, despite increasing exposure, there remains substantial confusion about what AI actually is, what it can reasonably do, and where its limitations begin.This gap between availability and understanding carries clinical, ethical, and professional risks [2].A useful starting point is to clarify AI systems anatomy.Artificial intelligence is not a single tool but an umbrella term covering multiple system types.Traditional rule-based expert systems operate on fixed rules and do not learn.Machine
DOI: 10.15403/jgld-6827
Author: Bogdan Surdea-Blaga
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7140866871
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