Novel machine-learning techniques to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for glioblastoma
Making cancer treatment less toxic with the help of machine learning - science news

Cancer patients must often endure a combination of radiation therapy and multiple drugs taken every month, which leads to a variety of adverse effects. In a quest to minimize the toxic effects of cancer drugs, a team of scientists used a machine-learning algorithm in order to identify the minimum dose of drugs that is less dangerous, but still effective. In simulated trials of 50 patients, the machine-learning model designed treatment cycles that reduced the potency to a quarter or half of nearly all the doses while maintaining the same tumor-shrinking potential. Many times, it skipped doses altogether, scheduling administrations only twice a year instead of monthly.

Read the full story: MIT