Papers

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2003
Morgeson, F. P., & Campion, M. A.. (2003). Handbook of psychology work design (I. B. Weiner, Ed.). https://doi.org/10.1002/0471264385.wei1217
Morgeson, F. P., & Campion, M. A.. (2003). Work design. In W. Borman, Ilgen, D., & Klimoski, R. (Eds.), Handbook of Psychology: Industrial and Organizational Psychology (pp. 423–452). Hoboken, NY: Wiley.
2005
Baudoin, F., Bretier, P., & Corruble, V.. (2005). A dialogue agent with adaptive and proactive capabilities. In IEEE/WIC/ACM International Conference on Intelligent Agent TechnologyIEEE/WIC/ACM International Conference on Intelligent Agent Technology (293 - 296). https://doi.org/10.1109/IAT.2005.8
2013
Silva, F. N., Rodrigues, F. A., Oliveira, O. N., & L. Costa, daF.. (2013). Quantifying the interdisciplinarity of scientific journals and fields. Journal Of Informetrics, 7(2), 469 - 477. https://doi.org/10.1016/j.joi.2013.01.007
2015
Crews, A. (2015). The big move toward big data in employment. In Employment& Labor Law Solutions Worldwide. Retrieved de https://www.littler.com/files/wp_big_data_8-04-15.pdf
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
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
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
Clément, M., & Guitton, M. J.. (2015). Users’ reactions to actions of automated programs in Wikipedia. Computers In Human Behavior, 50, 66 - 75. https://doi.org/10.1016/j.chb.2015.03.078
2016
Colbert, A., Yee, N., & George, G.. (2016). The digital workforce and the workplace of the future. Academy Of Management Journal, 59(3), 731 - 739. https://doi.org/10.5465/amj.2016.4003
Storey, M. - A., & Zagalsky, A.. (2016). Disrupting developer productivity one bot at a time (T. Zimmermann, Cleland-Huang, J., & Su, Z., Trans.). In the 2016 24th ACM SIGSOFT International SymposiumProceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016 (928 - 931). https://doi.org/10.1145/2950290.2983989
Cascio, W. F., & Montealegre, R.. (2016). How technology is changing work and organizations. Annual Review Of Organizational Psychology And Organizational Behavior, 3(1), 349 - 375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Cockshott, P., & Renaud, K.. (2016). Humans, robots and values. Technology In Society, 45, 19 - 28. https://doi.org/10.1016/j.techsoc.2016.01.002
Johnson, A. E. W., Ghassemi, M. M., Nemati, S., Niehaus, K. E., Clifton, D., & Clifford, G. D.. (2016). Machine learning and decision support in critical care. Proceedings Of The Ieee, 104(2), 444 - 466. https://doi.org/10.1109/JPROC.2015.2501978
Johnson, A. E. W., Ghassemi, M. M., Nemati, S., Niehaus, K. E., Clifton, D., & Clifford, G. D.. (2016). Machine learning and decision support in critical care. Proceedings Of The Ieee, 104(2), 444 - 466. https://doi.org/10.1109/JPROC.2015.2501978
2017
Crowston, K., Østerlund, C., & Lee, T. Kyoung. (2017). Blending machine and human learning processes. In Hawai'i International Conference on System Sciences. https://doi.org/10.24251/HICSS.2017.009
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Cruz-Roa, A., Gilmore, H., Basavanhally, A., Feldman, M., Ganesan, S., Shih, N. N. C., et al.. (2017). A deep learning approach for quantifying tumor extent. Scientific Reports, 7(1). https://doi.org/10.1038/srep46450

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