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Impressive research at using to figure out the fewest and smallest doses of medication that could still be effective to treat .

By studying patient data, A.I. can limit toxicity in cancer treatment In a bid to improve quality of life for cancer patients, a team of researchers at the Massachusetts Institute of Technology have turned to machine learning to help avoid toxicity from cancer medications. The researchers are specifically targeting glioblastoma, the most aggressive form of brain cance...

“Delays in results 'affecting patient care', e.g. due to shortage of radiologists”, a conclusion of the Suggested solution: national reporting standards. But will this be feasible with increasing workload of radiologists?

X-ray result delays 'affect patient care' The health regulator found huge variations in the time taken to report on radiology examinations.

What do you do when you don't have enough to train your ? You build a neural network to create "artificial images" and train on those!

AI algorithm generates 'artificial' medical images Researchers from Canada have developed an artificial intelligence (AI) algorithm capable of generating "artificial" x-ray images that look just like the real thing. The artificial images can be used to train other AI algorithms in analyzing real medical images.

will strongly influence the practical reality of . Many opportunities arise, but there are also challenges we need to overcome. Read 's blogpost to learn more at https://t.co/TN75RJIxBS

Deep learning: its potential and challenges in radiology AI Medical image analysis Deep Learning is rapidly gaining ground. Research groups increasingly apply Deep Learning, and radiology AI companies are starting to implement the first Deep Learning software meant for practical use in the clinics.