Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions
Brigham and Women's Hospital · Harvard University · +4 more institutions
Abstract
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field. SIGNIFICANCE: AI is increasingly being applied to all aspects of oncology, where several applications are…
Citation impact
- FWCI
- 54.75
- Percentile
- 100%
- References
- 207
Authors
6- WLWilliam Lotter
Brigham and Women's Hospital, Harvard University, Dana-Farber Cancer Institute
- MJMichael J. Hassett
Harvard University, Dana-Farber Cancer Institute
- NSNikolaus Schultz
Memorial Sloan Kettering Cancer Center
- KLKenneth L. Kehl
Harvard University, Dana-Farber Cancer Institute
- EMEliezer M. Van Allen
Broad Institute, Harvard University, Dana-Farber Cancer Institute
Topics & keywords
- Modalities
- Field (mathematics)
- Data science
- Data integration
- Computer science
- Radiation oncology
- Artificial intelligence
- Medical physics