Papers
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. (2019). Artificial Intelligence and the Future of the Drug Safety Professional. Drug Safety, 42(4), 491 - 497. https://doi.org/10.1007/s40264-018-0746-z
. (2019). Artificial Intelligence and the Future of the Drug Safety Professional. Drug Safety, 42(4), 491 - 497. https://doi.org/10.1007/s40264-018-0746-z
. (2019). Benefits and risks of artificial intelligence tools in workplaces (Vol. 11581, pp. 292 - 315; ). In (Vol. 11581, pp. 292 - 315). https://doi.org/10.1007/978-3-030-22216-1_22
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal Of Cancer, 111, 148 - 154. https://doi.org/10.1016/j.ejca.2019.02.005
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task. European Journal Of Cancer, 113, 47 - 54. https://doi.org/10.1016/j.ejca.2019.04.001
. (2019). Does automation influence career decisions among South African students? (). In the South African Institute of Computer Scientists and Information Technologists 2019Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019 on ZZZ - SAICSIT '19 (1 - 10). https://doi.org/10.1145/335110810.1145/3351108.3351137
. (2019). Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots. Social Sciences, 8(5), 143. https://doi.org/10.3390/socsci8050143
. (2019). Emotional processes in human-robot interaction during brief cognitive testing. Computers In Human Behavior, 90, 331 - 342. https://doi.org/10.1016/j.chb.2018.08.013
. (2019). Emotional processes in human-robot interaction during brief cognitive testing. Computers In Human Behavior, 90, 331 - 342. https://doi.org/10.1016/j.chb.2018.08.013
. (2019). Fairer but not fair enough on the equitability of knowledge tracing. In the 9th International ConferenceProceedings of the 9th International Conference on Learning Analytics & Knowledge - LAK19 (335 - 339). https://doi.org/10.1145/3303772.3303838
. (2019). The future of health care: Protocol for measuring the potential of task automation grounded in the national health service primary care system. Jmir Research Protocols, 8(4), e11232. https://doi.org/10.2196/11232
. (2019). The future of human-AI collaboration: A taxonomy of design knowledge for hybrid intelligence systems. In Hawaii International Conference on System Sciences (HICSS). Presented at the Hawaii International Conference on System Sciences (HICSS). Retrieved de https://www.alexandria.unisg.ch/publications/254994
. (2019). The future of the work in America. In McKinsey Global Institute. Retrieved de https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow
. (2019). Governance of artificial intelligence and personal health information. Digital Policy, Regulation And Governance, 21(3), 280 - 290. https://doi.org/10.1108/DPRG-08-2018-0048
. (2019). Hybrid Intelligence. Business & Information Systems Engineering, 61(5), 637 - 643. https://doi.org/10.1007/s12599-019-00595-2