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Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. Marco. (2019). Hybrid Intelligence. Business & Information Systems Engineering, 61(5), 637 - 643. https://doi.org/10.1007/s12599-019-00595-2
Ebel, P., Söllner, M., Leimeister, J. Marco, Crowston, K., & de Vreede, G. - J.. (2021). Hybrid intelligence in business networks. Electronic Markets. https://doi.org/10.1007/s12525-021-00481-4
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Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., & Elhadad, N.. (2015). Intelligible Models for HealthCare (L. Cao, Zhang, C., Joachims, T., Webb, G., Margineantu, D. D., & Williams, G., Trans.). 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
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Seeber, I., Bittner, E., Briggs, R. O., de Vreede, T., de Vreede, G. Jan, Elkins, A., et al.. (2020). Machines as teammates: A research agenda on AI in team collaboration. Information And Management, 57, 103174. https://doi.org/10.1016/j.im.2019.103174
Carter, J., & Dewan, P.. (2015). Mining programming activity to promote help (pp. 23 - 42; N. Boulus-Rødje, Ellingsen, G., Bratteteig, T., Aanestad, M., & Bjørn, P., Eds.). In (pp. 23 - 42). https://doi.org/10.1007/978-3-319-20499-4_2
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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
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
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Basso, P., Chiaretti, G., Krzywdzinski, M., Gerber, C., & Evers, M.. (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
Metcalfe, J. S., Marathe, A. R., Haynes, B., Paul, V. J., Gremillion, G. M., Drnec, K., et al.. (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
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Eustace, S. (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
Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K.. (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
Edwards, C., Edwards, A., Spence, P. R., & Shelton, A. K.. (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
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Tsvetkova, M., Yasseri, T., Meyer, E. T., J. Pickering, B., Engen, V., Walland, P., et al.. (2017). Understanding human-machine networks. Acm Computing Surveys, 50(1), 1 - 35. https://doi.org/10.1145/3039868
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