Papers
Export 11 results:
Filters: First Letter Of Last Name is F [Clear All Filters]
AI and the Economy. https://doi.org/10.3386/w24689
. (2018). AI risk mitigation through democratic governance ( ). In the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES '18 (366 - 367). https://doi.org/10.1145/3278721.3278801
. (2018). “Algorithm” and “formula”. Communications Of The Acm, 9(4), 243. https://doi.org/10.1145/365278.365286
. (1966). Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review. Journal Of Affective Disorders, 241, 519-532. https://doi.org/10.1016/j.jad.2018.08.073
. (2018). . (2018).
. (2017).
Artificial intelligence: Implications for social inflation and insurance. Risk Management And Insurance Review, 21(3), 373 - 387. https://doi.org/10.1111/rmir.12111
. (2018). Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers. Industrial Management & Data Systems, 119(7), 1411 - 1430. https://doi.org/10.1108/IMDS-08-2018-0368
. (2019). Automation and the Division of Labor. Social Problems, 13(2), 149 - 160. https://doi.org/10.2307/798900
. (1965). Automation, computerization and future employment in Singapore. Southeast Asian Economies, 34(2), 388 - 399. https://doi.org/10.1355/ae34-2h
. (2017). Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study ( ). In Workshop on Engineering Applications (WEA 2017): Applied Computer Sciences in Engineering (pp. 65 - 71). https://doi.org/10.1007/978-3-319-66963-2_7
. (2017). Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study ( ). In Workshop on Engineering Applications (WEA 2017): Applied Computer Sciences in Engineering (pp. 65 - 71). https://doi.org/10.1007/978-3-319-66963-2_7
. (2017). Autonomous vehicles employment impact study. In Australia & New Zealand Driverless Vehicle Initiate. Retrieved de https://advi.org.au/wp-content/uploads/2018/09/Autonomous-Vehicles-Employment-Impact-Survey-COR050918-5.pdf
. (2018). Beyond Dyadic Interactions: Considering Chatbots as Community Members ( ). In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19 (1-13). https://doi.org/10.1145/3290605
. (2019). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
. (2018). 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
. (2017). Collaboration and delegation between humans and AI: An experimental investigation of the future of work. Ssrn Electronic Journal. https://doi.org/10.2139/ssrn.3368813
. (2019). A comparison between human–human online conversations and human–chatbot conversations. Computers In Human Behavior, 49, 245 - 250. https://doi.org/10.1016/j.chb.2015.02.026
. (2015). A comparison between human–human online conversations and human–chatbot conversations. Computers In Human Behavior, 49, 245 - 250. https://doi.org/10.1016/j.chb.2015.02.026
. (2015). 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). Debating big data: A literature review on realizing value from big data. The Journal Of Strategic Information Systems, 26(3), 191 - 209. https://doi.org/10.1016/j.jsis.2017.07.003
. (2017). A deep learning approach for quantifying tumor extent. Scientific Reports, 7(1). https://doi.org/10.1038/srep46450
. (2017). 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).