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De Fauw, Jeffrey; Ledsam, Joseph R; Romera-Paredes, Bernardino; Nikolov, Stanislav; Tomasev, Nenad; Blackwell, Sam; Askham, Harry; Glorot, Xavier; O'Donoghue, Brendan; Visentin, Daniel; van den Driessche, George; Lakshminarayanan, Balaji; Meyer, Clemens; Mackinder, Faith; Bouton, Simon; Ayoub, Kareem; Chopra, Reena; King, Dominic; Karthikesalingam, Alan; Hughes, Cían O; Raine, Rosalind; Hughes, Julian; Sim, Dawn A; Egan, Catherine; Tufail, Adnan; Montgomery, Hugh; Hassabis, Demis; Rees, Geraint; Back, Trevor; Khaw, Peng T; Suleyman, Mustafa; Cornebise, Julien; Keane, Pearse A; Ronneberger, Olaf
Nature medicine, 09/2018, Letnik: 24, Številka: 9Journal Article
The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common diseases and typically relies on databases of millions of annotated images. Until now, the challenge of reaching the performance of expert clinicians in a real-world clinical pathway with three-dimensional diagnostic scans has remained unsolved. Here, we apply a novel deep learning architecture to a clinically heterogeneous set of three-dimensional optical coherence tomography scans from patients referred to a major eye hospital. We demonstrate performance in making a referral recommendation that reaches or exceeds that of experts on a range of sight-threatening retinal diseases after training on only 14,884 scans. Moreover, we demonstrate that the tissue segmentations produced by our architecture act as a device-independent representation; referral accuracy is maintained when using tissue segmentations from a different type of device. Our work removes previous barriers to wider clinical use without prohibitive training data requirements across multiple pathologies in a real-world setting.
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Dostop do baze podatkov JCR je dovoljen samo uporabnikom iz Slovenije. Vaš trenutni IP-naslov ni na seznamu dovoljenih za dostop, zato je potrebna avtentikacija z ustreznim računom AAI.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Povezave do osebnih bibliografij avtorjev | Povezave do podatkov o raziskovalcih v sistemu SICRIS |
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Vir: Osebne bibliografije
in: SICRIS
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