Research progress of artificial intelligence and machine learning in pulmonary embolism

被引：0

作者：

Li, Yue ^{[1
]}

Zhang, Limin ^{[1
]}

Liu, Haoran ^{[2
]}

Li, Yanxia ^{[1
]}

Liu, Zhuo ^{[1
]}

机构：

[1] Dalian Med Univ, Affiliated Hosp 1, Dept Pulm & Crit Care Med, Dalian, Peoples R China

[2] Dalian Med Univ, Dalian, Peoples R China

来源：

FRONTIERS IN MEDICINE | 2025年 / 12卷

关键词：

artificial intelligence; machine learning; pulmonary embolism; prediction; diagnosis; prognosis; THROMBOEMBOLIC EVENTS; EMERGENCY-DEPARTMENT; COMPUTED-TOMOGRAPHY; RISK STRATIFICATION; D-DIMER; VALIDATION; PREDICTION; CONTRAST; MODEL; DERIVATION;

D O I：

10.3389/fmed.2025.1577559

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

The pathophysiology and clinical manifestations of pulmonary embolism are complex, heterogeneous, and the disease burden is severe, and its prediction and diagnosis are of major challenges. Artificial intelligence (AI) is a field of computer science that involves the development of programs and complex data analysis designed to replicate human cognitive processes. In recent years, with the continuous development of medical information technology, the application of AI in the diagnosis and treatment of diseases has made rapid progress, especially in the field of pulmonary embolism, which is mainly based on imaging. In this review, we summarize the current application prospects and directions of AI in early prediction, screening, diagnosis, and prognosis of PE, and discuss the main challenges and future of AI in pulmonary embolism (PE), in order to provide a theoretical basis for the application of AI in the risk assessment and standardized management of PE.

引用

页数：8

共 97 条

[1] Development and Validation of a Natural Language Processing Model to Identify Low-Risk Pulmonary Embolism in Real Time to Facilitate Safe Outpatient Management [J].

Amin, Krunal D. ;

Weissler, Elizabeth Hope ;

Ratliff, William ;

Sullivan, Alexander E. ;

Holder, Tara A. ;

Bury, Cathleen ;

Francis, Samuel ;

Theiling, Brent Jason ;

Hintze, Bradley ;

Gao, Michael ;

Nichols, Marshall ;

Balu, Suresh ;

Jones, William Schuyler ;

Sendak, Mark .

ANNALS OF EMERGENCY MEDICINE, 2024, 84 (02) :118-127

[2] Radiomics machine learning study with a small sample size: Single random training-test set split may lead to unreliable results [J].

An, Chansik ;

Park, Yae Won ;

Ahn, Sung Soo ;

Han, Kyunghwa ;

Kim, Hwiyoung ;

Lee, Seung-Koo .

PLOS ONE, 2021, 16 (08)

[3] Nonthrombotic Pulmonary Embolism From Inorganic Particulate Matter and Foreign Bodies [J].

Asah, Derick ;

Raju, Shine ;

Ghosh, Subha ;

Mukhopadhyay, Sanjay ;

Mehta, Atul C. .

CHEST, 2018, 153 (05) :1249-1265

[4] Derivation and validation of a prognostic model for pulmonary embolism [J].

Aujesky, D ;

Obrosky, DS ;

Stone, RA ;

Auble, TE ;

Perrier, A ;

Cornuz, J ;

Roy, PM ;

Fine, MJ .

AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2005, 172 (08) :1041-1046

[5] Machine Learning for Clinical Chemists [J].

Badrick, Tony ;

Banfi, Giuseppe ;

Bietenbeck, Andreas ;

Cervinski, Mark A. ;

Loh, Tze Ping ;

Sikaris, Ken .

CLINICAL CHEMISTRY, 2019, 65 (11) :1350-1356

[6] Development and Performance of the Pulmonary Embolism Result Forecast Model (PERFORM) for Computed Tomography Clinical Decision Support [J].

Banerjee, Imon ;

Sofela, Miji ;

Yang, Jaden ;

Chen, Jonathan H. ;

Shah, Nigam H. ;

Ball, Robyn ;

Mushlin, Alvin, I ;

Desai, Manisha ;

Bledsoe, Joseph ;

Amrhein, Timothy ;

Rubin, Daniel L. ;

Zamanian, Roham ;

Lungren, Matthew P. .

JAMA NETWORK OPEN, 2019, 2 (08)

[7] Age-sex specific pulmonary embolism-related mortality in the USA and Canada, 2000-18: an analysis of the WHO Mortality Database and of the CDC Multiple Cause of Death database [J].

Barco, Stefano ;

Valerio, Luca ;

Ageno, Walter ;

Cohen, Alexander T. ;

Goldhaber, Samuel Z. ;

Hunt, Beverley J. ;

Iorio, Alfonso ;

Jimenez, David ;

Klok, Frederikus A. ;

Kucher, Nils ;

Mahmoudpour, Seyed Hamidreza ;

Middeldorp, Saskia ;

Munzel, Thomas ;

Tagalakis, Vicky ;

Wendelboe, Aaron M. ;

Konstantinides, Stavros, V .

LANCET RESPIRATORY MEDICINE, 2021, 9 (01) :33-42

[8] Detection of Incidental Pulmonary Embolism on Conventional Contrast-Enhanced Chest CT: Comparison of an Artificial Intelligence Algorithm and Clinical Reports [J].

Batra, Kiran ;

Xi, Yin ;

Al-Hreish, Khaled M. ;

Kay, Fernando U. ;

Browning, Travis ;

Baker, Chris ;

Peshock, Ronald M. .

AMERICAN JOURNAL OF ROENTGENOLOGY, 2022, 219 (06) :895-902

[9] Artificial Intelligence in Medicine [J].

Beam, Andrew L. ;

Drazen, Jeffrey M. ;

Kohane, Isaac S. ;

Leong, Tze-Yun ;

Manrai, Arjun K. ;

Rubin, Eric J. .

NEW ENGLAND JOURNAL OF MEDICINE, 2023, 388 (13) :1220-1221

[10] Big Data and Machine Learning in Health Care [J].

Beam, Andrew L. ;

Kohane, Isaac S. .

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2018, 319 (13) :1317-1318

← 1 2 3 4 5 6 7 8 9 10 →