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Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, (77). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, (77). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, (77). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, (77). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, 7(1). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, 7(1). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, 7(1). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR). Systematic Reviews, 7(1). https://doi.org/10.1186/s13643-018-0740-7
. (2018). Integration of people, technology and organization: the european approach. In International Conference on Human-Computer Interaction (HCI International) (pp. 957-961). Tokyo, Japan: Elsevier.
. (1995). Human resource technology disruptions and their implications for human resources management in healthcare organizations. Bmc Health Services Research, 19(1). https://doi.org/10.1186/s12913-019-4068-3
. (2019). How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany ( ). In Electronic Government (pp. 233-247). https://doi.org/10.1007/978-3-030-27325-5
. (2019). . (2017).
. (2019).
How artificial intelligence will redefine management. Havard Business Review. Retrieved de https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management
. (2016). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea
. (2017). The Future of Work: Robots Cooking Free Lunches?. European View, 17(2), 241 - 241. https://doi.org/10.1177/1781685818813010
. (2018). . (2016).
An experimental comparison of Chatbot and Human task partners. Computers In Human Behavior, 75, 461 - 468. https://doi.org/10.1016/j.chb.2017.05.045
. (2017). Does AI qualify for the job? A bidirectional model mapping labour and AI intensities. In AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (94–100). https://doi.org/10.1145/3375627.3375831
. (2020). Digital Economics. Journal Of Economic Literature, 57(1), 3 - 43. https://doi.org/10.1257/jel.20171452
. (2019). . (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). 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). 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).