A study analyzing AI-driven mammogram interpretation found a significant increase in research, with the number of studies rising from 28 in 2017-2018 to 115 in 2022-2023, marking a 311% increase. Despite this growth, only 0-25% of these studies reported on the race or ethnicity of participants, with most patients identified as Caucasian. The research, which reviewed 5,774 studies and included 264 in its analysis, highlighted a lack of diversity in both datasets and researcher representation. Nearly all patient cohorts were from high-income countries, and no studies originated from low-income settings. The study warns that this lack of diversity could undermine the fairness and generalizability of AI models used in mammogram interpretation. It suggests that algorithms primarily trained on Caucasian populations might lead to inaccurate outcomes and misdiagnoses in underrepresented groups, potentially worsening existing disparities in patient outcomes.
Eric Topol
@EricTopol
·
Feb 3 The largest medical #AI randomized controlled trial yet performed, enrolling >100,000 women undergoing mammography screening, was published today
@LancetDigitalH
The use of A.I. led to 29% higher detection of cancer, no increase of false positives, and reduced workload compared
Chiara Corti
@CCortiMD
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23h “Global disparities in artificial intelligence-based mammogram interpretation for breast cancer: A scientometric analysis of representation, trends, and equity” https://shorturl.at/Q7xFo . A #thread
Sunil Thakur
@thakur_sunil
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Apr 10 Two different studies indicating how AI systems can slowly prove to be better than or assistive to humans in diagnosis and consults.The research method has limitations but gives a good directional perspective.Study announced in two
@Nature
publications is part of Project AMIE
EMJ Reviews
@EMJReviews
·
Apr 9 Generative AI is revolutionising radiology workflows.A new model trained on over 8 million radiographs delivers high-quality reports with 83.2% sensitivity, excelling in detecting critical conditions.Find out more:
Annals of Surgery
@AnnalsofSurgery
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Apr 7 AI is transforming breast cancer care . A new noninvasive system predicts residual cancer burden early during neoadjuvant chemotherapy, helping tailor treatment strategies. A step toward more personalized oncology.
@RadiologyEditor
@RadiologyEditor
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Apr 8 Can AI outperform radiologists in detecting contralateral breast cancers after unilateral mastectomy? A study by
@jungmin_chang
&
@SuMinHa2
found standalone AI had higher detection rates and sensitivity than radiologists. Check it out! #Radiology
https://pubs.rsna.org/doi/10.1148/radiol.242955…
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