Research progress of artificial intelligence and machine learning in pulmonary embolism
Yue Li1, Limin Zhang1, Haoran Liu2
1Department of Pulmonary and Critical Care Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, China.
Frontiers in Medicine
|April 11, 2025
Summary
Artificial intelligence (AI) offers promising solutions for complex pulmonary embolism (PE) diagnosis and management. This review explores AI
Area of Science:
- Medical imaging analysis
- Computational pathology
- Health informatics
Background:
- Pulmonary embolism (PE) presents complex pathophysiology and diagnostic challenges.
- Severe disease burden necessitates improved prediction and management strategies.
- Advancements in medical technology are driving AI applications in healthcare.
Purpose of the Study:
- To review the current applications of Artificial Intelligence (AI) in pulmonary embolism (PE).
- To explore AI's role in early prediction, screening, diagnosis, and prognosis of PE.
- To discuss the future directions and challenges of AI in PE management.
Main Methods:
- Literature review of AI applications in PE diagnosis and treatment.
- Analysis of AI's potential in imaging-based PE detection.
- Synthesis of current research on AI for PE risk assessment and management.
Main Results:
- AI shows significant potential in enhancing early prediction and screening for PE.
- AI-powered tools can improve the accuracy and efficiency of PE diagnosis, particularly from imaging data.
- AI applications are emerging for prognostic assessment and personalized management of PE patients.
Conclusions:
- AI holds considerable promise for revolutionizing the early detection, diagnosis, and management of pulmonary embolism.
- Further research and development are needed to overcome challenges and fully integrate AI into clinical practice for PE.
- AI can provide a theoretical foundation for improved risk stratification and standardized care in PE.
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