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Deep learning model to predict exercise stress test results: Optimizing the diagnostic test selection strategy and reduce wastage in suspected coronary artery disease patients.
Lu J, Stewart J, Bennamoun M, Goudie A, Eshraghian J, Ihdayhid A, Sanfilippo F, Small GR, Chow BJ, Dwivedi G. Lu J, et al. Among authors: sanfilippo f. Comput Methods Programs Biomed. 2023 Oct;240:107717. doi: 10.1016/j.cmpb.2023.107717. Epub 2023 Jul 9. Comput Methods Programs Biomed. 2023. PMID: 37454499 Free article.
Machine learning in heart failure: ready for prime time.
Awan SE, Sohel F, Sanfilippo FM, Bennamoun M, Dwivedi G. Awan SE, et al. Among authors: sanfilippo fm. Curr Opin Cardiol. 2018 Mar;33(2):190-195. doi: 10.1097/HCO.0000000000000491. Curr Opin Cardiol. 2018. PMID: 29194052 Review.
Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation.
Lu J, Hutchens R, Hung J, Bennamoun M, McQuillan B, Briffa T, Sohel F, Murray K, Stewart J, Chow B, Sanfilippo F, Dwivedi G. Lu J, et al. Among authors: sanfilippo f. Comput Biol Med. 2022 Nov;150:106126. doi: 10.1016/j.compbiomed.2022.106126. Epub 2022 Sep 22. Comput Biol Med. 2022. PMID: 36206696
628 results