AI model learns how to make cancer treatment less toxic #hcsmeufr #esante #digitalhealth | GAFAMS, STARTUPS & INNOVATION IN HEALTHCARE by PHARMAGEEK | Scoop.it

The MIT researchers say that their AI model may improve cancer patients’ quality of life. The researchers are investigating how it may reduce toxic radiotherapy and chemotherapy dosing for glioblastoma.
Prognosis for adults with glioblastoma is up to five years. In other words, patients rarely live longer than five years after diagnosis. They have to endure a combination of multiple medications and radiation therapy.

Doctors generally administer maximum safe drug doses to shrink tumors as much as possible. However, they are powerful drugs which cause debilitating side effects in patients.
The AI model ‘learns’ from patient data, and subsequently makes cancer treatment considerably less toxic.
 MIT Media Lab researchers are presenting their research at the 2018 Machine Learning for Healthcare Conference at Stanford University.

The AI model is powered by a ‘self-learning‘ machine-learning technique. It looks at treatment regimes that are currently in use and iteratively adjusts their doses. 
It eventually finds an optimal treatment plan. The plan has the lowest possible potency and dose frequency without losing efficacy. In this context, efficacy refers to the treatment’s ability to shrink tumors.