How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases?

被引：3

作者：

Hoang-Thi, Trieu-Nghi ^{[1
]}

Chassagnon, Guillaume ^{[2
]}

Tran, Hai-Dang ^{[1
]}

Le-Dong, Nhat-Nam ^{[3
]}

Dinh-Xuan, Anh Tuan ^{[3
]}

Revel, Marie-Pierre ^{[2
]}

机构：

[1] Vinmec Healthcare Syst, Dept Diagnost Imaging, Ho Chi Minh City 70000, Vietnam

[2] Univ Paris, Cochin Hosp, AP HP Ctr, Dept Radiol, F-75005 Paris, France

[3] Univ Paris, Cochin Hosp, AP HP Ctr, Dept Resp Physiol, F-75005 Paris, France

来源：

JOURNAL OF PERSONALIZED MEDICINE | 2022年 / 12卷 / 09期

关键词：

artificial intelligence; bronchial disease; parenchymal lung disease; machine learning; IDIOPATHIC PULMONARY-FIBROSIS; QUANTITATIVE COMPUTED-TOMOGRAPHY; CT INDEXES; QUANTIFICATION; DIAGNOSIS; CLASSIFICATION; ASSOCIATION; EMPHYSEMA; PATTERNS; AIRWAYS;

D O I：

10.3390/jpm12091429

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

With the rapid development of computing today, artificial intelligence has become an essential part of everyday life, with medicine and lung health being no exception. Big data-based scientific research does not mean simply gathering a large amount of data and letting the machines do the work by themselves. Instead, scientists need to identify problems whose solution will have a positive impact on patients' care. In this review, we will discuss the role of artificial intelligence from both physiological and anatomical standpoints, starting with automatic quantitative assessment of anatomical structures using lung imaging and considering disease detection and prognosis estimation based on machine learning. The evaluation of current strengths and limitations will allow us to have a broader view for future developments.

引用

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