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pro vyhledávání: '"Rasalingham, Simon"'
AIM To analyse the performance of a deep-learning (DL) algorithm currently deployed as diagnostic decision support software in two NHS Trusts used to identify normal chest x-rays in active clinical pathways. MATERIALS AND METHODS A DL algorithm has b
Externí odkaz:
http://arxiv.org/abs/2306.16115
Autor:
Dyer, Tom, Smith, Jordan, Dissez, Gaetan, Tay, Nicole, Malik, Qaiser, Morgan, Tom Naunton, Williams, Paul, Garcia-Mondragon, Liliana, Pearse, George, Rasalingham, Simon
Purpose: Artificial intelligence (AI) solutions for medical diagnosis require thorough evaluation to demonstrate that performance is maintained for all patient sub-groups and to ensure that proposed improvements in care will be delivered equitably. T
Externí odkaz:
http://arxiv.org/abs/2209.09204
Autor:
Dissez, Gaetan, Tay, Nicole, Dyer, Tom, Tam, Matthew, Dittrich, Richard, Doyne, David, Hoare, James, Pat, Jackson J., Patterson, Stephanie, Stockham, Amanda, Malik, Qaiser, Morgan, Tom Naunton, Williams, Paul, Garcia-Mondragon, Liliana, Smith, Jordan, Pearse, George, Rasalingham, Simon
Objectives: The present study evaluated the impact of a commercially available explainable AI algorithm in augmenting the ability of clinicians to identify lung cancer on chest X-rays (CXR). Design: This retrospective study evaluated the performance
Externí odkaz:
http://arxiv.org/abs/2208.14742
Akademický článek
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Autor:
Dyer, Tom, Chawda, Sanjiv, Alkilani, Raed, Morgan, Tom Naunton, Hughes, Mike, Rasalingham, Simon
Publikováno v:
Neuroradiology; Apr2022, Vol. 64 Issue 4, p735-743, 9p
