Papers

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D
Davenport, T., & Kalakota, R.. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94 - 98. https://doi.org/10.7861/futurehosp.6-2-94
Dolata, M., Crowston, K., & Schwabe, G.. (2022). Project archetypes: A blessing and a curse for AI development. In International Conference on Information Systems (ICIS). Presented at the International Conference on Information Systems (ICIS), Copenhagen, Denmark. Retrieved de https://aisel.aisnet.org/icis2022/is_design/is_design/6
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M
Malone, T. W., Nickerson, J. V., Laubacher, R. J., Fisher, L. Hesse, de Boer, P., Han, Y., & Ben Towne, W.. (2017). Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (1661–1674). https://doi.org/10.1145/2998181.2998343
Metcalf, L., Askay, D. A., & Rosenberg, L. B.. (2019). Pooling knowledge through artificial swarm intelligence to improve business decision making. California Management Review, 61(4), 84 - 109. https://doi.org/10.1177/0008125619862256
O
Obermeyer, Z., & Emanuel, E. J.. (2016). Predicting the Future — Big Data, Machine Learning, and Clinical Medicine. New England Journal Of Medicine, 375(13), 1216 - 1219. https://doi.org/10.1056/NEJMp1606181
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Raj, M., & Seamans, R.. (2019). Primer on artificial intelligence and robotics. Journal Of Organization Design, 8(1). https://doi.org/10.1186/s41469-019-0050-0
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Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038
Sampson, S. (2020). Predicting Automation of Professional Jobs in Healthcare. In Proceedings of the 53rd Hawaii International Conference on System Sciences (3, 3529–3537). https://doi.org/10.24251/hicss.2020.433