Application of Artificial Intelligence in Thoracic Radiology: A Narrative Review

被引：0

作者：

Lim, Woo Hyeon ^{[1
]}

Kim, Hyungjin ^{[1
,2
]}

机构：

[1] Seoul Natl Univ Hosp, Dept Radiol, Seoul, South Korea

[2] Seoul Natl Univ, Coll Med, Dept Radiol, 101 Daehak Ro, Seoul 03080, South Korea

来源：

TUBERCULOSIS AND RESPIRATORY DISEASES | 2025年 / 88卷 / 02期

关键词：

Artificial Intelligence; Deep Learning; Thoracic Radiology; OBSTRUCTIVE PULMONARY-DISEASE; LARGE LANGUAGE MODELS; LUNG-CANCER; QUANTITATIVE CT; CLASSIFICATION; TUBERCULOSIS; MULTICENTER; IMAGES; AI;

D O I：

10.4046/trd.2024.0062

中图分类号：

R56 [呼吸系及胸部疾病];

学科分类号：

摘要：

Thoracic radiology has emerged as a primary field in which artificial intelligence (AI) is extensively researched. Recent advancements highlight the potential to enhance radiologists' performance through AI. AI aids in detecting and classifying abnormalities, and in quantifying both normal and abnormal anatomical structures. Additionally, it facilitates prognostication by leveraging these quantitative values. This review article will discuss the recent achievements of AI in thoracic radiology, focusing primarily on deep learning, and explore the current limitations and future directions of this cutting-edge technique.

引用

页码：278 / 291

页数：14

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