Cancer survival predicted by AI reading oncologists' notes. medtwitter healthtech AI
First author John-Jose Nunez, MD, a psychiatrist and clinical research fellow at the UBC Mood Disorders Centre and BC Cancer, Vancouver, Canada, was pleasantly surprised by his team's results:"I thought they would be pretty good [but] I think they were even a bit better than we expected."
"Essentially, everybody receiving cancer care is going to have one of these documents. So this is really easy to use for a wide group of people and for us to keep building the models and treating it with more data. That's a big advantage." The reports are in English, generated by dictation, and consist of simple paragraphs with headings, BC Cancer's standard format for initial consultation notes, according to Nunez.
It's similar to how physicians learn, said Nunez."Throughout med school residency we need to see thousands and thousands of patients, lots and lots of data, to train our own neural networks inside our brain," he said."The nice thing is that AI can train much quicker...a couple of days to go through 30,000-plus patients."
Although the Canadian team has not yet compared the performance of their model to that of humans, US researchers showed last year that AI can outperform oncologists — at least for 3-month survival in certain cancers.that showed their machine-learning model was 60% accurate at predicting 3-month mortality in patients with metastatic solid tumors overall versus 35% in the case of oncologists .
"If there's a time that we want to know the patient's preferences, values, and priorities – that would be now," said Zachariah.
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