5 machine learning algorithms ID lymphedema among breast cancer patients

Researchers utilized five different machine learning approaches to accurately spot lymphedema--a negative side effect of breast cancer treatment--which may help detect it earlier and improve treatment. The study was published in the May edition of the journal mHealth. "Using a well-trained classification algorithm to detect lymphedema based on real-time symptom reports is a highly promising tool that may improve lymphedema outcomes," said lead author Mei R Fu, PhD, and associate professor of nursing at New York University in an NYU release. A web-based tool collected information from 355 women who had undergone treatment for breast cancer, including surgery. Participants shared demographic data and clinical information and were asked if they were experiencing any 26 different lymphedema-related symptoms.