Papers
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. (2014). Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers In Human Behavior, 33, 372 - 376. https://doi.org/10.1016/j.chb.2013.08.013
. (2014). Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter. Computers In Human Behavior, 33, 372 - 376. https://doi.org/10.1016/j.chb.2013.08.013
. (2015). Intelligible Models for HealthCare (). In the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15 (1721 - 1730). https://doi.org/10.1145/278325810.1145/2783258.2788613
. (2015). Mining programming activity to promote help (pp. 23 - 42; ). In (pp. 23 - 42). https://doi.org/10.1007/978-3-319-20499-4_2
. (2016). Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning. Computers In Human Behavior, 65, 666 - 671. https://doi.org/10.1016/j.chb.2016.07.003
. (2016). Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning. Computers In Human Behavior, 65, 666 - 671. https://doi.org/10.1016/j.chb.2016.07.003
. (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
. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542, 115–118.
. (2017). An empirical analysis of the impacts of robotization on employment in the Norwegian manufacturing industry. In Administration, Economics. Retrieved de https://www.semanticscholar.org/paper/Will-robots-replace-us-%3A-an-Empirical-analysis-of-Gr%C3%B8ndahl-Eriksen/e4e22bf2498e42d6308d81cc7483b5a0b8ba48e7
. (2017). SPIE ProceedingsBuilding a framework to manage trust in automation. In SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX (10194, 101941U). https://doi.org/10.1117/12.2264245
. (2017). Understanding human-machine networks. Acm Computing Surveys, 50(1), 1 - 35. https://doi.org/10.1145/3039868
. (2018). Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide (Vol. 537, pp. 359 - 373; ). In (Vol. 537, pp. 359 - 373). https://doi.org/10.1007/978-3-319-99605-9_27
. (2018). Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide (Vol. 537, pp. 359 - 373; ). In (Vol. 537, pp. 359 - 373). https://doi.org/10.1007/978-3-319-99605-9_27
. (2018). Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration. Philosophical Transactions Of The Royal Society A: Mathematical, Physical And Engineering Sciences, 376(2128), 20170357. https://doi.org/10.1098/rsta.2017.0357
. (2018). Automating the black art: Creative places for artificial intelligence in audio mastering. Geoforum, 96, 77-86. https://doi.org/10.1016/j.geoforum.2018.08.005
. (2018). The economics of artificial intelligence: Implications for the future of work. In International Labour Office. Retrieved de https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_647306.pdf
. (2018). Robots worldwide: The impact of automation on employment and trade. In International Labour Office. Retrieved de https://www.ilo.org/wcmsp5/groups/public/---dgreports/---inst/documents/publication/wcms_648063.pdf
. (2018). The social consequences of the digital revolution (Vol. 6). In (Vol. 6). https://doi.org/10.30687/2610-968910.30687/978-88-6969-273-410.30687/978-88-6969-273-4/008
. (2018). Technology-induced bias in the theory of evidence-based medicine. Journal Of Evaluation In Clinical Practice, 24(5), 945 - 949. https://doi.org/10.1111/jep.12972
. (2019). Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark. European Journal Of Cancer, 111, 30 - 37. https://doi.org/10.1016/j.ejca.2018.12.016
. (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