Papers

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2019
Lysaght, T., Lim, H. Yeefen, Xafis, V., & Ngiam, K. Yuan. (2019). AI-Assisted Decision-making in Healthcare. Asian Bioethics Review, 11(3), 299 - 314. https://doi.org/10.1007/s41649-019-00096-0
Nichols, J. A., Chan, H. W. Herbert, & Baker, M. A. B.. (2019). Applications of artificial intelligence to imaging and diagnosis. Biophysical Reviews, 11(1), 111 - 118. https://doi.org/10.1007/s12551-018-0449-9
Nam, T. (2019). Citizen attitudes about job replacement by robotic automation. Futures, 109, 39 - 49. https://doi.org/10.1016/j.futures.2019.04.005
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
Kittur, A., Yu, L., Hope, T., Chan, J., Lifshitz-Assaf, H., Gilon, K., et al.. (2019). Scaling up analogical innovation with crowds and AI. Proceedings Of The National Academy Of Sciences, 116(6), 1870-1877. https://doi.org/10.1073/pnas.1807185116
2018
Gries, T., & Naude, W.. (2018). Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter. In Maastricht Economic and social Research institute on Innovation and Technology. Retrieved de http://ftp.iza.org/dp12005.pdf
Nathan, L. F. (2018). Creativity, the arts, and the future of work (pp. 283 - 310; J. W. Cook, Ed.). In (pp. 283 - 310). https://doi.org/10.1007/978-3-319-78580-6_9
Data Science for Undergraduates. (2018). Data Science for Undergraduates. https://doi.org/10.17226/25104
Avati, A., Jung, K., Harman, S., Downing, L., Ng, A., & Shah, N. H.. (2018). Improving palliative care with deep learning. Bmc Medical Informatics And Decision Making, 18(S4). https://doi.org/10.1186/s12911-018-0677-8
Winn, A. N., & Neuner, J. M.. (2018). Making Sure We Don’t Forget the Basics When Using Machine Learning. Jnci: Journal Of The National Cancer Institute, 111(6), 529 - 530. https://doi.org/10.1093/jnci/djy179
Winn, A. N., & Neuner, J. M.. (2018). Making Sure We Don’t Forget the Basics When Using Machine Learning. Jnci: Journal Of The National Cancer Institute, 111(6), 529 - 530. https://doi.org/10.1093/jnci/djy179
2017
Neyland, D., & Möllers, N.. (2017). Algorithmic IF  … THEN rules and the conditions and consequences of power. Information, Communication & Society, 20(1), 45 - 62. https://doi.org/10.1080/1369118X.2016.1156141
Shen, S., & Neyens, D. M.. (2017). Assessing drivers' response during automated driver support system failures with non-driving tasks. Journal Of Safety Research, 61, 149 - 155. https://doi.org/10.1016/j.jsr.2017.02.009
Di Prospera, A., norouzi, N., Fokaefs, M., & Litoiu, M.. (2017). Chatbots as assistants, an architectural framework. In CASCON '17 Proceedings of the 27th Annual International Conference on Computer Science and Software Engineering. Retrieved de https://dl.acm.org/citation.cfm?id=3172805

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