Papers
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. (2018). Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review. Journal Of Affective Disorders, 241, 519-532. https://doi.org/10.1016/j.jad.2018.08.073
. (2018). Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review. Journal Of Affective Disorders, 241, 519-532. https://doi.org/10.1016/j.jad.2018.08.073
. (2018). Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review. Journal Of Affective Disorders, 241, 519-532. https://doi.org/10.1016/j.jad.2018.08.073
. (2011). Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. Journal Of Informetrics, 5(1), 14 - 26. https://doi.org/10.1016/j.joi.2010.06.004
. (2011). Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature. Journal Of Informetrics, 5(1), 14 - 26. https://doi.org/10.1016/j.joi.2010.06.004
. (2022). Artificial intelligence in information systems: State of the art and research roadmap. Communications Of The Association For Information Systems (Cais), 50. https://doi.org/10.17705/1CAIS.05017
Artificial Intelligence in Information Systems State of the Art.pdf (1 MB). (2018). Artificial Intelligence in Service. Journal Of Service Research, 21(2), 155 - 172. https://doi.org/10.1177/1094670517752459
. (2018). Artificial intelligence, machine learning and the evolution of healthcare A bright future or cause for concern?. British Journal Of Radiology, 7(7), 223-225.
. (2018). Artificial intelligence, machine learning and the evolution of healthcare. Bone & Joint Research, 7(3), 223 - 225. https://doi.org/10.1302/2046-3758.73.BJR-2017-0147.R1
. (2018). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
. (2018). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
. (2002). Can we ever escape from data overload? A cognitive systems diagnosis. Cognition, Technology & Work, 4(1), 22 - 36. https://doi.org/10.1007/s101110200002
. (2020). A Cautionary Tale for Machine Learning Design: why we Still Need Human-Assisted Big Data Analysis. Mobile Networks And Applications, 25, 1075–1083. https://doi.org/10.1007/s11036-020-01530-6
. (2020). Competing with Robots: Firm-Level Evidence from France. Aea Papers And Proceedings, 110, 383–388. https://doi.org/10.1257/pandp.20201003
. (2002). Converging technologies for improving human performance: Integrating from the nanoscale. Journal Of Nanoparticle Research, 4(4), 281-295. Retrieved de https://link.springer.com/article/10.1023/A:1021152023349
. (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). 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
. (2018). Digital economy and the models of income distribution in the society. Shs Web Of Conferences, 44, 00005. https://doi.org/10.1051/shsconf/20184400005
. (2017). Employment, inequality and ethics in the digital age. The Ippr Commission On Economic Justice. Retrieved de https://www.ippr.org/publications/managing-automation
. (2020). Engaged to a Robot? The Role of AI in Service. Journal Of Service Research. https://doi.org/10.1177/1094670520902266
. (2020). Feminist economic geography and the future of work. Epa: Economy And Space, 1–12. https://doi.org/10.1177/0308518X20947101