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The Evolution of the Brain From Analog to Digital: The Birth of Artificial Intelligence.

The Journal of craniofacial surgery 2026 Vol.37(3-4) p. 782-787 Artificial Intelligence in Healthcar
TL;DR This review outlines the evolution of machine learning from handcrafted feature extraction to deep representation learning, explains the fundamental principles of transformer architecture and probabilistic text generation, and summarizes current applications of LLMs within plastic and reconstructive surgery.
OpenAlex 토픽 · Artificial Intelligence in Healthcare and Education Anatomy and Medical Technology Machine Learning in Healthcare

Nahass GR, Patel PK

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【연구 목적】 인공지능(AI) 기술의 급속한 발전과 함께 언어, 이미지, 다중 임상 데이터를 처리하는 시스템의 진화 배경을 설명한다.

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BibTeX ↓ RIS ↓
APA George R. Nahass, Pravin K. Patel (2026). The Evolution of the Brain From Analog to Digital: The Birth of Artificial Intelligence.. The Journal of craniofacial surgery, 37(3-4), 782-787. https://doi.org/10.1097/SCS.0000000000012364
MLA George R. Nahass, et al.. "The Evolution of the Brain From Analog to Digital: The Birth of Artificial Intelligence.." The Journal of craniofacial surgery, vol. 37, no. 3-4, 2026, pp. 782-787.
PMID 41773846

Abstract

Recent advances in artificial intelligence (AI) have accelerated the development of systems capable of processing language, images, and multimodal clinical data with unprecedented scale. Among these, transformer-based large language models (LLMs) such as GPT-4 represent a major conceptual leap in how computers learn and generate human language. This review outlines the evolution of machine learning from handcrafted feature extraction to deep representation learning, explains the fundamental principles of transformer architecture and probabilistic text generation, and summarizes current applications of LLMs within plastic and reconstructive surgery. Emerging studies demonstrate promise in automated documentation, resident education, and patient communication, yet also highlight limitations, including hallucinations, bias, and the need for rigorous validation. This review aims to provide clinicians (particularly plastic surgeons) with a concise overview of model structure, training paradigms, and practical considerations for future usage of AI in clinical medicine.

추출된 의학 개체 (NER)

유형영어 표현한국어 / 풀이UMLS CUI출처등장
해부 Brain scispacy 1
약물 GPT-4 scispacy 1
질환 hallucinations C0018524
Hallucinations
scispacy 1
기타 human scispacy 1

MeSH Terms

Humans; Artificial Intelligence; Brain; Machine Learning; Surgery, Plastic; Deep Learning

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