Editorial: Advances in artificial intelligence and machine learning applications for the imaging of bone and soft tissue tumors
2024
Advances in AI and Machine Learning for Imaging Tumors
Editorial
Author Information
Author(s): Fields Brandon K. K., Varghese Bino A., Matcuk George R. Jr
Primary Institution: University of California, San Francisco
Conclusion
This Research Topic highlights innovative developments in AI and machine learning applications for the imaging of bone and soft tissue neoplasms.
Supporting Evidence
- AI applications in medical imaging have surged, with over 33,000 publications in 2023 alone.
- Machine learning models have shown promise in detecting pelvic bone metastases.
- Deep learning segmentation methods are crucial for evaluating malignant bone tumors.
- Emerging AI applications include lesion detection and treatment response assessment.
- Federated learning may help in training models without compromising patient data.
Takeaway
Researchers are using smart computer programs to help doctors see and understand tumors better, which can lead to better treatment for patients.
Potential Biases
Potential conflicts of interest due to authors' affiliations and funding sources.
Limitations
Challenges include assembling large, diverse datasets and managing complex data systems.
Digital Object Identifier (DOI)
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