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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 critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; ). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18
. (2018). A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; ). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18
. (2018). A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; ). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18
. (2018). A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force (Vol. 10963, pp. 217 - 232; ). In (Vol. 10963, pp. 217 - 232). https://doi.org/10.1007/978-3-319-95171-3_18
. (2018). Data tracking in search of workflows ( ). In the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17 (2153 - 2165). https://doi.org/10.1145/2998181.2998296
. (2017). Datification, organizational strategy, and is research: What’s the score? . The Journal Of Strategic Information Systems, 26(3), 233 - 241. https://doi.org/10.1016/j.jsis.2017.08.003
. (2017). Debating big data: A literature review on realizing value from big data. The Journal Of Strategic Information Systems, 26(3), 191 - 209. https://doi.org/10.1016/j.jsis.2017.07.003
. (2017). A deep learning approach for quantifying tumor extent. Scientific Reports, 7(1). https://doi.org/10.1038/srep46450
. (2017). Deep learning for healthcare: review, opportunities and challenges. Briefings In Bioinformatics, 19(6), 1236 - 1246. https://doi.org/10.1093/bib/bbx044
. (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). 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). 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). 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). Degree of Automation in Command and Control Decision Support Systems. In IEEE International Conference on Systems, Man and Cybernetics. Presented at the IEEE International Conference on Systems, Man and Cybernetics. Retrieved de https://ieeexplore.ieee.org/document/7844402
. (2016). Degree of Automation in Command and Control Decision Support Systems. In IEEE International Conference on Systems, Man and Cybernetics. Presented at the IEEE International Conference on Systems, Man and Cybernetics. Retrieved de https://ieeexplore.ieee.org/document/7844402
. (2016).