Next Article in Journal
Problem-Solving Treatment for People Recently Diagnosed with Visual Impairment: Pilot Randomised Controlled Trial
Previous Article in Journal
MiRNA as a Potential Target for Multiple Myeloma Therapy–Current Knowledge and Perspectives
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JPM
Volume 12
Issue 9
10.3390/jpm12091429
jpm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

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

by
Trieu-Nghi Hoang-Thi
1,*,
Guillaume Chassagnon
2,
Hai-Dang Tran
1,
Nhat-Nam Le-Dong
3,
Anh Tuan Dinh-Xuan
3 and
Marie-Pierre Revel
2
1
Department of Diagnostic Imaging, Vinmec Healthcare System, Ho Chi Minh City 70000, Vietnam
2
AP-HP. Centre, Cochin Hospital, Department of Radiology, Université de Paris, 75005 Paris, France
3
AP-HP. Centre, Cochin Hospital, Department of Respiratory Physiology, Université de Paris, 75005 Paris, France
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2022, 12(9), 1429; https://doi.org/10.3390/jpm12091429
Submission received: 12 August 2022 / Revised: 25 August 2022 / Accepted: 26 August 2022 / Published: 31 August 2022
(This article belongs to the Section Mechanisms of Diseases)
Browse Figures
Review Reports Versions Notes

Abstract

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.
Keywords: artificial intelligence; bronchial disease; parenchymal lung disease; machine learning artificial intelligence; bronchial disease; parenchymal lung disease; machine learning

Share and Cite

MDPI and ACS Style

Hoang-Thi, T.-N.; Chassagnon, G.; Tran, H.-D.; Le-Dong, N.-N.; Dinh-Xuan, A.T.; Revel, M.-P. How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases? J. Pers. Med. 2022, 12, 1429. https://doi.org/10.3390/jpm12091429

AMA Style

Hoang-Thi T-N, Chassagnon G, Tran H-D, Le-Dong N-N, Dinh-Xuan AT, Revel M-P. How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases? Journal of Personalized Medicine. 2022; 12(9):1429. https://doi.org/10.3390/jpm12091429

Chicago/Turabian Style

Hoang-Thi, Trieu-Nghi, Guillaume Chassagnon, Hai-Dang Tran, Nhat-Nam Le-Dong, Anh Tuan Dinh-Xuan, and Marie-Pierre Revel. 2022. "How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases?" Journal of Personalized Medicine 12, no. 9: 1429. https://doi.org/10.3390/jpm12091429

APA Style

Hoang-Thi, T.-N., Chassagnon, G., Tran, H.-D., Le-Dong, N.-N., Dinh-Xuan, A. T., & Revel, M.-P. (2022). How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases? Journal of Personalized Medicine, 12(9), 1429. https://doi.org/10.3390/jpm12091429

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop