Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review
Pulmonary embolism (PE) remains a critical condition with significant mortality and morbidity, necessitating timely detection and intervention to improve patient outcomes. This review examines the evolving role of artificial intelligence (AI) in PE management. Two primary AI-driven models that are c...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/15/7/889 |
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| author | Ahmad Moayad Naser Rhea Vyas Ahmed Ashraf Morgan Abdul Mukhtadir Kalaiger Amrin Kharawala Sanjana Nagraj Raksheeth Agarwal Maisha Maliha Shaunak Mangeshkar Nikita Singh Vikyath Satish Sheetal Mathai Leonidas Palaiodimos Robert T. Faillace |
| author_facet | Ahmad Moayad Naser Rhea Vyas Ahmed Ashraf Morgan Abdul Mukhtadir Kalaiger Amrin Kharawala Sanjana Nagraj Raksheeth Agarwal Maisha Maliha Shaunak Mangeshkar Nikita Singh Vikyath Satish Sheetal Mathai Leonidas Palaiodimos Robert T. Faillace |
| author_sort | Ahmad Moayad Naser |
| collection | DOAJ |
| description | Pulmonary embolism (PE) remains a critical condition with significant mortality and morbidity, necessitating timely detection and intervention to improve patient outcomes. This review examines the evolving role of artificial intelligence (AI) in PE management. Two primary AI-driven models that are currently being explored are deep convolutional neural networks (DCNNs) for enhanced image-based detection and natural language processing (NLP) for improved risk stratification using electronic health records. A major advancement in this field was the FDA approval of the Aidoc© AI model, which has demonstrated high specificity and negative predictive value in PE diagnosis from imaging scans. Additionally, AI is being explored for optimizing anticoagulation strategies and predicting PE recurrence risk. While further large-scale studies are needed to fully establish AI’s role in clinical practice, its integration holds significant potential to enhance diagnostic accuracy and overall patient management. |
| format | Article |
| id | doaj-art-b5fcab0f619c4fea81d6e56f0ff20f30 |
| institution | DOAJ |
| issn | 2075-4418 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj-art-b5fcab0f619c4fea81d6e56f0ff20f302025-08-20T03:06:29ZengMDPI AGDiagnostics2075-44182025-04-0115788910.3390/diagnostics15070889Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive ReviewAhmad Moayad Naser0Rhea Vyas1Ahmed Ashraf Morgan2Abdul Mukhtadir Kalaiger3Amrin Kharawala4Sanjana Nagraj5Raksheeth Agarwal6Maisha Maliha7Shaunak Mangeshkar8Nikita Singh9Vikyath Satish10Sheetal Mathai11Leonidas Palaiodimos12Robert T. Faillace13Department of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, Montefiore Wakefield Medical Center, New York, NY 10461, USADepartment of Cardiology, University of Nebraska Medical Center, Omaha, NE 68198, USADepartment of Cardiology, Montefiore Medical Center, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Cardiology, Montefiore Medical Center, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USADepartment of Medicine, New York City Health + Hospitals/Jacobi, Albert Einstein College of Medicine, New York, NY 10461, USAPulmonary embolism (PE) remains a critical condition with significant mortality and morbidity, necessitating timely detection and intervention to improve patient outcomes. This review examines the evolving role of artificial intelligence (AI) in PE management. Two primary AI-driven models that are currently being explored are deep convolutional neural networks (DCNNs) for enhanced image-based detection and natural language processing (NLP) for improved risk stratification using electronic health records. A major advancement in this field was the FDA approval of the Aidoc© AI model, which has demonstrated high specificity and negative predictive value in PE diagnosis from imaging scans. Additionally, AI is being explored for optimizing anticoagulation strategies and predicting PE recurrence risk. While further large-scale studies are needed to fully establish AI’s role in clinical practice, its integration holds significant potential to enhance diagnostic accuracy and overall patient management.https://www.mdpi.com/2075-4418/15/7/889artificial intelligenceartificial neural networksdeep convolutional neural networks (DCNN)machine learningnatural language processing (NLP)pulmonary embolism |
| spellingShingle | Ahmad Moayad Naser Rhea Vyas Ahmed Ashraf Morgan Abdul Mukhtadir Kalaiger Amrin Kharawala Sanjana Nagraj Raksheeth Agarwal Maisha Maliha Shaunak Mangeshkar Nikita Singh Vikyath Satish Sheetal Mathai Leonidas Palaiodimos Robert T. Faillace Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review Diagnostics artificial intelligence artificial neural networks deep convolutional neural networks (DCNN) machine learning natural language processing (NLP) pulmonary embolism |
| title | Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review |
| title_full | Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review |
| title_fullStr | Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review |
| title_full_unstemmed | Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review |
| title_short | Role of Artificial Intelligence in the Diagnosis and Management of Pulmonary Embolism: A Comprehensive Review |
| title_sort | role of artificial intelligence in the diagnosis and management of pulmonary embolism a comprehensive review |
| topic | artificial intelligence artificial neural networks deep convolutional neural networks (DCNN) machine learning natural language processing (NLP) pulmonary embolism |
| url | https://www.mdpi.com/2075-4418/15/7/889 |
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