New AI technique to make cancer treatment less toxic

New AI technique to make cancer treatment less toxic

By: IANS | New York |

Published: August 11, 2018 8:33:21 pm

Medicine, Cancer, Clinical medicine, Oncology, RTT, Brain tumor, Cancer treatments, Aging-associated diseases, Chemotherapy, Radiation therapy, Post-chemotherapy cognitive impairment, Adjuvant therapy, Educational Services, Pratik Shah, Massachusetts Institute The findings will be presented at the 2018 Machine Learning for Healthcare conference at Stanford University in California. (Image: Getty)

MIT researchers, including one of Indian-origin, have developed novel machine-learning techniques to improve the quality of life for patients by reducing toxic chemotherapy and radiotherapy dosing for an aggressive form of brain cancer. Glioblastoma is a malignant tumour that appears in the brain or spinal cord, and the prognosis for adults is no more than five years. Patients are generally administered maximum safe drug doses to shrink the tumour as much as possible, but they still remain at risk of debilitating side effects.

The new “self-learning” machine-learning technique could make the dosing regimen less toxic but still effective. It looks at the treatment regimen currently in use, and finds an optimal treatment plan, with the lowest possible potency and frequency of doses that should still reduce tumour sizes to a degree comparable to that of traditional regimen, the researchers said.

“We kept the goal where we have to help patients by reducing tumour sizes but, at the same time, we want to make sure the quality of life — the dosing toxicity — doesn’t lead to overwhelming sickness and harmful side effects,” said Pratik Shah, principal investigator from the Massachusetts Institute of Technology (MIT) in Boston, US.

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