Based on the information you provided, here are some articles related to the application of Artificial Intelligence in diagnosing diseases, primarily focusing on developments in Europe from the years 2015-2023. Note that some articles may require a subscription or purchase to access in full: Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115–118. Rajkomar, A., Oren, E., Chen, K., Dai, A. M., Hajaj, N., Hardt, M., Liu, P. J., Liu, X., Marcus, J., Sun, M., Sundberg, P., Yee, H., Zhang, K., Zhang, Y., Flores, G., Duggan, G. E., Irvine, J., Le, Q., Litsch, K., Mossin, A., Tansuwan, J., Wang, D., Wexler, J., Wilson, J., Ludwig, D., Volchenboum, S. L., Chou, K., Pearson, M., Madabushi, S., Shah, N. H., Butte, A. J., Howell, M. D., Cui, C., Corrado, G. S., & Dean, J. (2018). Scalable and accurate deep learning with electronic health records. NPJ Digital Medicine, 1(1), 18. Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. McDermott, M. B., Wang, Y., Yan, A., Png, E., Albiges, L., Zimmermann, B., Harari, A., Zhao, J., & Lee, C. H. (2020). Clinical-grade computational pathology using weakly supervised deep learning on whole slide images. Nature Medicine, 26(8), 1301–1309. Meyer, A., Zverinski, D., Pfahringer, B., Kempfert, J., Kuehne, T., Sündermann, S. H., Stamm, C., Hofmann, T., Falk, V., Eickhoff, C., & Fattinger, S. (2018). Machine learning for real-time prediction of complications in critical care: a retrospective study. The Lancet Respiratory Medicine, 6(12), 905–914. [Titano, J. J., Badgeley, M., Schefflein, J., Pain, M., Su, A., Cai, M., Swinburne, N., Zech, J., Kim, J., Bederson, J., Mocco, J., & Drakopoulos, P. (2018). Automated deep-neural-network surveillance of cranial images for acute neurologic events. Nature Medicine,