Crowdsourced AI learns to target lung tumors for radiation

- In many parts of the world there are not enough radiation oncologists to design and deliver radiation treatments for lung cancer patients, but that gap could one day be filled with the help of artificial intelligence, researchers suggest in a new study.

"You take your medical imaging - there can be 100 images that are slices through the tumor - and hand-draw on each slice where the tumor is," Mak explained."Then you draw in where the organs are. And then you determine how to aim the radiation." In this case, the researchers had US$50,000 in prize money to offer coders who could come up with"new AI techniques that could train machines to replicate an expert clinician's ability to target a tumor," Mak said.

"We compared the performance of the algorithms, that is, compared algorithm-generated versus the human expert to generate a performance score on each case, and then benchmarked against the variation seen between multiple human experts against the study's expert, and also the intra-observer variation, that is the same expert doing the same task twice," Mak said."The ensemble of the best algorithms had overlap scores in 75 percent of the cases that matched intra-observer score.

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