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Predicting conversion to wet age-related macular degeneration using deep learning.
Yim J, Chopra R, Spitz T, Winkens J, Obika A, Kelly C, Askham H, Lukic M, Huemer J, Fasler K, Moraes G, Meyer C, Wilson M, Dixon J, Hughes C, Rees G, Khaw PT, Karthikesalingam A, King D, Hassabis D, Suleyman M, Back T, Ledsam JR, Keane PA, De Fauw J. Yim J, et al. Nat Med. 2020 Jun;26(6):892-899. doi: 10.1038/s41591-020-0867-7. Epub 2020 May 18. Nat Med. 2020. PMID: 32424211
A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis.
Liu X, Faes L, Kale AU, Wagner SK, Fu DJ, Bruynseels A, Mahendiran T, Moraes G, Shamdas M, Kern C, Ledsam JR, Schmid MK, Balaskas K, Topol EJ, Bachmann LM, Keane PA, Denniston AK. Liu X, et al. Lancet Digit Health. 2019 Oct;1(6):e271-e297. doi: 10.1016/S2589-7500(19)30123-2. Epub 2019 Sep 25. Lancet Digit Health. 2019. PMID: 33323251 Free article.
Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study.
Faes L, Wagner SK, Fu DJ, Liu X, Korot E, Ledsam JR, Back T, Chopra R, Pontikos N, Kern C, Moraes G, Schmid MK, Sim D, Balaskas K, Bachmann LM, Denniston AK, Keane PA. Faes L, et al. Lancet Digit Health. 2019 Sep;1(5):e232-e242. doi: 10.1016/S2589-7500(19)30108-6. Epub 2019 Sep 5. Lancet Digit Health. 2019. PMID: 33323271 Free article.