aceArtificial Intelligence for Prediction of Breast Cancer-Related Lymphedema: A Systematic Review
Background Breast cancer-related lymphedema (BCRL) impairs quality of life and function, and early detection is crucial for preventive intervention. AI models, particularly machine learning and deep learning, hold promise for improving BCRL prediction and personalized risk stratification. This systematic review evaluates AI applications for predicting BCRL and, where available, summarizes how their reported performance compared with traditional diagnostic or non-AI methods. Methods This systematic review followe…
Across five studies reporting classification results, AI models predicted breast cancer-related lymphedema with a mean accuracy of 87.2%, mean sensitivity of 85.5%, and mean specificity of 87.6%.
The same BCRL prediction models have small samples, heterogeneous data, no external validation, and inconsistent calibration, so they are not yet clinically established.
The authors state that current models are exploratory, limited by small samples, heterogeneous data, absent external validation, and inconsistent calibration, so prospective validation is needed before clinical use.
Evidence
- Peer-reviewedPlastic and Reconstructive Surgery - Global Open2026-10-06
How should this claim be treated?
Truvace Impact Record TRV-2026-1792, v1: “Artificial Intelligence for Prediction of Breast Cancer-Related Lymphedema: A Systematic Review.” Truvace, 2026-10-18. /record/TRV-2026-1792 (accessed at citation time). sha256 c4c96278481d762c…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1792 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.