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AI can jump-start radiation therapy for cancer patients

Woman pointing to projection of brain scan while talking to man
Dr. Mu-Han Lin, left, consults with Dr. Steve Jiang about a radiation treatment plan developed by artificial intelligence. Dr. Jiang's team trained four deep-learning models to instantly generate dosage plans and shorten the time patients must wait before starting radiation therapy.

Artificial intelligence can help cancer patients start their radiation therapy sooner – and thereby decrease the odds of the cancer spreading – by instantly translating complex clinical data into an optimal plan of attack.

Patients typically must wait several days to a week to begin therapy while doctors manually develop treatment plans. But new research from UT Southwestern shows how enhanced deep-learning models streamlined this process down to a fraction of a second.

“Some of these patients need radiation therapy immediately, but doctors often have to tell them to go home and wait,” said Dr. Steve Jiang, who directs UT Southwestern’s Medical Artificial Intelligence and Automation (MAIA) Lab. “Achieving optimal treatment plans in near real time is important and part of our broader mission to use AI to improve all aspects of cancer care.”

Visit the UT Southwestern Newsroom to read the full story.

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