Editor's Note
A computer model, which for the first time accurately predicted two of the most challenging side effects of radiation therapy for head and neck cancer patients, was presented September 26 at the Annual Meeting of the American Society for Radiation Oncology in Chicago.
Researchers from the University of Texas MD Anderson Cancer Center used machine learning, a branch of artificial intelligence (AI), to develop models to analyze large sets of data merged from three sources: electronic health records, an internal web-based charting tool, and a record/verify system.
The models predicted the likelihood of significant weight loss and need for feeding tube placement with a high degree of accuracy.
Being able to identify which patients are at greatest risk would help radiation oncologists prevent or mitigate these side effects, the authors say.
