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Rachita Mallya

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Articles

Diagnostic accuracy, fairness and clinical implementation of AI for breast cancer screening: results of multicenter retrospective and prospective technical feasibility studies

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By Christopher Kelly, Marc Wilson, Lucy Warren, Richard Sidebottom, Mark Halling-Brown, Lin Yang, Jenny Venton, Reena Chopra, Jane Chang, Jonathan Dixon, Fiona Gilbert, Daniel Golden Verified, Lesley Honeyfield, Emma Lewis, Namrata Malhotra, Della Ogunleye, Charlotte Purdy, Rory Sayres, Marcin Sieniek, Aminata Sy, Susan Thomas, Dominic Ward, Shawn Xu, Shravya Shetty, Ara Darzi, Kenneth R. Young, Hema Purushothaman, Mamatha M. Reddy, Hutan Ashrafian, Deborah Cunningham, Megumi Morigami, Elzbieta Gruzewska, Amandeep Hujan, Delara Khodabakhshi, Rachita Mallya, Tsvetina Stoycheva, Lihong Xi, Lisanne Khoo
| Nature Verified
Abstract Artificial intelligence (AI) promises to enhance breast cancer screening. Here we evaluated Google’s mammography AI system (version 1.2) across two phases: a retrospective study using 115,973 mammograms from five National Health Service screening services with 39-month follow-up and prospective noninterventional feasibility deployment at 12 sites (9,266 cases). The primary endpoint was AI sensitivity and specificity versus first reader using a 5% noninferiority margin.
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