RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists | Annals of Oncology https://t.co/f0mKSVHlFZ
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
This paper has an altimetric score >1000 <2 weeks after release. certainly one of the "must read" in the medical literature in 2018. https://t.co/4qxY0M3Idc
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists | Annals of Oncology | Oxford Academic https://t.co/rMQnTst1mm
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
AI is definitely here to augment human capabilities! https://t.co/61vWaX8O13
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
Deep Learning outperforms dermathologists in melanoma predictions https://t.co/6H64MU60L8
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
Man vs Machine. Machine outperforms man. https://t.co/XX3NGEJFFe
Great to see machines doing what humans aren't good at -- and don't like to do -- better and faster! Diagnostic performance was compared with a intl group of 58 dermatologists, including 30 experts. Irrespective of physicians’ experience, they may benefit
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±9.6%, P = 0.19) - specificity: 75.7% (±11.7%, P < 0.05).... https://t.co/Adj6yDglua [Yann LeCun] https://t.co/t7v2pKOJmz
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
RT @ylecun: ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±…
ConvNet outperforms human dermatologists for melanoma detection. Dermatologists in level-II protocol: - sensitivity: 88.9% (±9.6%, P = 0.19) - specificity: 75.7% (±11.7%, P < 0.05).... https://t.co/L3kmXgQufa
RT @RafikSmati: #SignesDuFutur : une Intelligence Artificielle se montre plus fiable pour diagnostiquer le cancer de la peau que 58 dermato…
RT @RafikSmati: #SignesDuFutur : une Intelligence Artificielle se montre plus fiable pour diagnostiquer le cancer de la peau que 58 dermato…
RT @RafikSmati: #SignesDuFutur : une Intelligence Artificielle se montre plus fiable pour diagnostiquer le cancer de la peau que 58 dermato…
RT @RafikSmati: #SignesDuFutur : une Intelligence Artificielle se montre plus fiable pour diagnostiquer le cancer de la peau que 58 dermato…
RT @RussellKohl: AI beats dermatologists in dermascopic diagnosis of melanoma-imagine that tool in the hands of patients or family docs htt…
AI beats dermatologists in dermascopic diagnosis of melanoma-imagine that tool in the hands of patients or family docs https://t.co/bMEEEgSHQS
RT @Clairefuller19: Dr Jacki Li challenges 2nd #WorldSkinSummit : is machine better than man at diagnosis? Future of AI @ILDSDerm @IFDerm h…
RT @Clairefuller19: Dr Jacki Li challenges 2nd #WorldSkinSummit : is machine better than man at diagnosis? Future of AI @ILDSDerm @IFDerm h…
Dr Jacki Li challenges 2nd #WorldSkinSummit : is machine better than man at diagnosis? Future of AI @ILDSDerm @IFDerm https://t.co/GmL6fwhCil
RT @RafikSmati: #SignesDuFutur : une Intelligence Artificielle se montre plus fiable pour diagnostiquer le cancer de la peau que 58 dermato…