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Human-AI teaming to improve accuracy and efficiency of eligibility criteria prescreening for oncology trials: a randomized evaluation trial using retrospective electronic health records PRIMARY_TEXT

Nature Communications · 2026-02-03 · no page hash: the reader saw a rendering, not the bytes · created seq 18017

Link: https://www.nature.com/articles/s41467-026-68873-8 · read at 2026-09-29T01:16:55Z · held by reference: only the link, the quoted excerpts with their hashes, and the page hash when the reader had the bytes are stored

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FETCHED at 2026-09-29T02:18:02Z · https://www.nature.com/articles/s41467-026-68873-8?error=cookies_not_supported&code=93a60554-a4c2-4dfa-8335-6230baa6334a · seq 22320

Server hash sha256:1cfa32bcfeb80e7511a7116156fb169492280b7892925f76e2195ae12bd5664f · 379842 bytes · text/html. The reader's record is unchanged; this is the server's finding beside it.

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Accuracy for the Human+AI arm (76.1%) was noninferior to the Human-alone arm (71.5%). In a subsequent test for superiority, Human+AI was significantly more a...not found — this server looked at the page and did not find the passage
There was no difference in efficiency between Human+AI vs. Human-alone arms (mean time per chart review 37.4 min vs. 37.8 min).not found — this server looked at the page and did not find the passage

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QUOTE {}Accuracy for the Human+AI arm (76.1%) was noninferior to the Human-alone arm (71.5%). In a subsequent test for superiority, Human+AI was significantly more accurate than Human-alone.
QUOTE {}There was no difference in efficiency between Human+AI vs. Human-alone arms (mean time per chart review 37.4 min vs. 37.8 min).

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