HIGHLIGHTS
SUMMARY
In this scenario, growing attention has been recently raised to machine_learning solutions in BC management, with promising implications in developing self-improving technological models to guide clinicians in a precision medicine approach. In more detail, the authors assessed a 26-item tool assessing self-reported symptoms, integrating a novel machine_learning algorithm in the diagnostic process of BCRL to promote an early and time-efficient detection of lymphedema status. Wei et_al developed a machine_learning algorithm based on 24 items and included lymphedema symptoms assessment to diagnose lymphedema. Despite the positive results of these studies, self . . .
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