@OpenMedFuture I‘m aware of this study and of the fact that human factors account for many errors in many fields of practice. But the assumption that AI will fix errors, or that it will be safer than human agency, is problematic (see also https://t.co/Hl1
Critical Review: Not all biases are bad - equitable and inequitable biases in #MachineLearning and #radiology. (Mirjam Pot et al.) #InsightsIntoImaging To read more, click here ➡️ https://t.co/4gKuwbQLLZ https://t.co/0TpDxly7gg
RT @cd_fuller: @Radiology_AI Scientifically, biased data is poorly generalizable, and bias in #AI data is a inequitable potential source of…
RT @cd_fuller: @Radiology_AI Scientifically, biased data is poorly generalizable, and bias in #AI data is a inequitable potential source of…
@Radiology_AI Scientifically, biased data is poorly generalizable, and bias in #AI data is a inequitable potential source of harm and injury at worst, and a performance obstacle at least. https://t.co/AkVyqcQDpb
RT @BPrainsack: “Medicine is based on an ideal of neutrality”: A. Iannessi et al’s criticism of our proposal to systematically consider ine…
RT @BPrainsack: “Medicine is based on an ideal of neutrality”: A. Iannessi et al’s criticism of our proposal to systematically consider ine…
RT @BPrainsack: “Medicine is based on an ideal of neutrality”: A. Iannessi et al’s criticism of our proposal to systematically consider ine…
RT @BPrainsack: “Medicine is based on an ideal of neutrality”: A. Iannessi et al’s criticism of our proposal to systematically consider ine…
“Medicine is based on an ideal of neutrality”: A. Iannessi et al’s criticism of our proposal to systematically consider inequities at all stages of machine learning in radiology: https://t.co/2n7wVIjDL8 (our original article: https://t.co/Hl1EX4TBeE) https
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @salvasapedraza: Pot, M., Kieusseyan, N. & Prainsack, B. Not all biases are bad: equitable and inequitable biases in machine learning an…
Pot, M., Kieusseyan, N. & Prainsack, B. Not all biases are bad: equitable and inequitable biases in machine learning and radiology. Insights Imaging 12, 13 (2021). https://t.co/bbizZzRhoJ
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @wyatt_sally: always worth reading @BPrainsack This looks super interesting for our #RAIDIO project - @FloraLysen @ALBredenoord @Jongsma…
RT @wyatt_sally: always worth reading @BPrainsack This looks super interesting for our #RAIDIO project - @FloraLysen @ALBredenoord @Jongsma…
always worth reading @BPrainsack This looks super interesting for our #RAIDIO project - @FloraLysen @ALBredenoord @JongsmaKr @ShokoVos & to be shared with Megan Milota & Jojanneke Drogt
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
RT @BPrainsack: New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @…
New paper: „Not all biases are bad: equitable and inequitable biases in machine learning and radiology“, with @mirjam_pot @NKieusseyan https://t.co/63Nxifrxz8 https://t.co/cQ1LtNAKvq