Research progress of artificial intelligence and machine learning in pulmonary embolism
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 comp...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-03-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1577559/full |
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| author | Yue Li Limin Zhang Haoran Liu Yanxia Li Zhuo Liu |
| author_facet | Yue Li Limin Zhang Haoran Liu Yanxia Li Zhuo Liu |
| author_sort | Yue Li |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-8524b57c1baf4b219dc606d24eb0a42e |
| institution | Kabale University |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj-art-8524b57c1baf4b219dc606d24eb0a42e2025-08-20T03:42:02ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-03-011210.3389/fmed.2025.15775591577559Research progress of artificial intelligence and machine learning in pulmonary embolismYue Li0Limin Zhang1Haoran Liu2Yanxia Li3Zhuo Liu4Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDalian Medical University, Dalian, ChinaDepartment of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, ChinaDepartment of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, ChinaThe 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.https://www.frontiersin.org/articles/10.3389/fmed.2025.1577559/fullartificial intelligencemachine learningpulmonary embolismpredictiondiagnosisprognosis |
| spellingShingle | Yue Li Limin Zhang Haoran Liu Yanxia Li Zhuo Liu Research progress of artificial intelligence and machine learning in pulmonary embolism Frontiers in Medicine artificial intelligence machine learning pulmonary embolism prediction diagnosis prognosis |
| title | Research progress of artificial intelligence and machine learning in pulmonary embolism |
| title_full | Research progress of artificial intelligence and machine learning in pulmonary embolism |
| title_fullStr | Research progress of artificial intelligence and machine learning in pulmonary embolism |
| title_full_unstemmed | Research progress of artificial intelligence and machine learning in pulmonary embolism |
| title_short | Research progress of artificial intelligence and machine learning in pulmonary embolism |
| title_sort | research progress of artificial intelligence and machine learning in pulmonary embolism |
| topic | artificial intelligence machine learning pulmonary embolism prediction diagnosis prognosis |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2025.1577559/full |
| work_keys_str_mv | AT yueli researchprogressofartificialintelligenceandmachinelearninginpulmonaryembolism AT liminzhang researchprogressofartificialintelligenceandmachinelearninginpulmonaryembolism AT haoranliu researchprogressofartificialintelligenceandmachinelearninginpulmonaryembolism AT yanxiali researchprogressofartificialintelligenceandmachinelearninginpulmonaryembolism AT zhuoliu researchprogressofartificialintelligenceandmachinelearninginpulmonaryembolism |