Papers
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. (2018). Robotic process automation. Business & Information Systems Engineering, 60(4), 269 - 272. https://doi.org/10.1007/s12599-018-0542-4
. (2018). Skill shift automation and the future of the workforce. In McKinsey Global Institute. Retrieved de https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce
. (2018). Social robots as cultural objects: The sixth dimension of dynamicity?. The Information Society, 34(3), 141 - 152. https://doi.org/10.1080/01972243.2018.1444253
. (2018). System architecture of a driverless electric car in the grand cooperative driving challenge. Ieee Intelligent Transportation Systems Magazine, 10(1), 47 - 59. https://doi.org/10.1109/MITS.2017.2776135
. (2018). Understanding Chatbot-mediated Task Management (). In the 2018 CHI ConferenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 (1 - 6). https://doi.org/10.1145/317357410.1145/3173574.3173632
. (2018). Will artificial intelligence solve the human resource crisis in healthcare?. Bmc Health Services Research, 18(1). https://doi.org/10.1186/s12913-018-3359-4
. (2019). AI-Based Digital Assistants. Business & Information Systems Engineering, 61(4), 535 - 544. https://doi.org/10.1007/s12599-019-00600-8
. (2019). AI-Based Digital Assistants. Business & Information Systems Engineering, 61(4), 535 - 544. https://doi.org/10.1007/s12599-019-00600-8
. (2019). 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). Bots Coordinating Work in Open Source Software Projects. Computer, 52(9), 52 - 60. https://doi.org/10.1109/MC.2018.2885970
. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5 - 14. https://doi.org/10.1177/0008125619864925
. (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). 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). 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). Consider the human work experience when integrating robotics in the workplace. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (75 - 84). https://doi.org/10.1109/HRI.2019.8673139
. (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
. (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
. (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