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In recent years, the number of machine learning (ML) technologies gaining regulatory approval for healthcare has increased significantly allowing them to be placed on the market. However, the regulatory frameworks applied to them were originally devi
Externí odkaz:
http://arxiv.org/abs/2209.00421
Autor:
Vasey, Baptiste, Nagendran, Myura, Campbell, Bruce, Clifton, David A, Collins, Gary S., Denaxas, Spiros, Denniston, Alastair K., Faes, Livia, Geerts, Bart, Ibrahim, Mudathir, Liu, Xiaoxuan, Mateen, Bilal A., Mathur, Piyush, Mccradden, Melissa D., Morgan, Lauren, Ordish, Johan, Rogers, Campbell, Saria, Suchi, Ting, Daniel S. W., Watkinson, Peter, Weber, Wim, Wheatstone, Peter, Mcculloch, Peter, Lee, Aaron Y., Fraser, Alan G., Connell, Ali, Vira, Alykhan, Esteva, Andre, Althouse, Andrew D., Beam, Andrew L., de Hond, Anne, Boulesteix, Anne-Laure, Bradlow, Anthony, Ercole, Ari, Paez, Arsenio, Tsanas, Athanasios, Kirby, Barry, Glocker, Ben, Velardo, Carmelo, Park, Chang Min, Hehakaya, Charisma, Baber, Chris, Paton, Chris, Johner, Christian, Kelly, Christopher J., Vincent, Christopher J., Yau, Christopher, Mcgenity, Clare, Gatsonis, Constantine, Faivre-Finn, Corinne, Simon, Crispin, Sent, Danielle, Bzdok, Danilo, Treanor, Darren, Clifton, David A., Wong, David C., Steiner, David F., Higgins, David, Benson, Dawn, O’Regan, Declan P., Gunasekaran, Dinesh V., Danks, Dominic, Neri, Emanuele, Kyrimi, Evangelia, Schwendicke, Falk, Magrabi, Farah, Ives, Frances, Rademakers, Frank E., Fowler, George E., Frau, Giuseppe, Hogg, H. D. Jeffry, Marcus, Hani J., Chan, Heang-Ping, Xiang, Henry, Mcintyre, Hugh F., Harvey, Hugh, Kim, Hyungjin, Habli, Ibrahim, Fackler, James C., Shaw, James, Higham, Janet, Wohlgemut, Jared M., Chong, Jaron, Bibault, Jean-Emmanuel, Cohen, Jérémie F., Kers, Jesper, Morley, Jessica, Krois, Joachim, Monteiro, Joao, Horovitz, Joel, Fletcher, John, Taylor, Jonathan, Yoon, Jung Hyun, Singh, Karandeep, Moons, Karel G. M., Karpathakis, Kassandra, Catchpole, Ken, Hood, Kerenza, Balaskas, Konstantinos, Kamnitsas, Konstantinos, Militello, Laura, Wynants, Laure, Oakden-Rayner, Lauren, Lovat, Laurence B., Smits, Luc J. M., Hinske, Ludwig C., Elzarrad, M. Khair, van Smeden, Maarten, Giavina-Bianchi, Mara, Daley, Mark, Sendak, Mark P., Sujan, Mark, Rovers, Maroeska, Decamp, Matthew, Woodward, Matthew, Komorowski, Matthieu, Marsden, Max, Mackintosh, Maxine, Abramoff, Michael D., de la Hoz, Miguel Ángel Armengol, Hambidge, Neale, Daly, Neil, Peek, Niels, Redfern, Oliver, Ahmad, Omer F., Bossuyt, Patrick M., Keane, Pearse A., Ferreira, Pedro N. P., Schnell-Inderst, Petra, Mascagni, Pietro, Dasgupta, Prokar, Guan, Pujun, Barnett, Rachel, Kader, Rawen, Chopra, Reena, Mann, Ritse M., Sarkar, Rupa, Mäenpää, Saana M., Finlayson, Samuel G., Vollam, Sarah, Vollmer, Sebastian J., Park, Seong Ho, Laher, Shakir, Joshi, Shalmali, van der Meijden, Siri L., Shelmerdine, Susan C., Tan, Tien-En, Stocker, Tom J. W., Giannini, Valentina, Madai, Vince I., Newcombe, Virginia, Wei Yan, Ng, Rogers, Wendy A., Ogallo, William, Park, Yoonyoung, Perkins, Zane B.
Publikováno v:
Nature Medicine, 28, 5, pp. 924-933
Nature Medicine, 28, 924-933
the DECIDE-AI expert group 2022, ' Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence : DECIDE-AI ', Nature Medicine, vol. 28, no. 5, pp. 924-933 . https://doi.org/10.1038/s41591-022-01772-9
Nature Medicine, 28, 924-933
the DECIDE-AI expert group 2022, ' Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence : DECIDE-AI ', Nature Medicine, vol. 28, no. 5, pp. 924-933 . https://doi.org/10.1038/s41591-022-01772-9
A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluati