¿Por qué la inteligencia artificial y el deep learning deben ir de la mano en la atención médica?

Referencias

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[2] Topol, E. (2019). Deep medicine: how artificial intelligence can make healthcare human again.  

[3] Aresta, G., Jacobs, C., Araújo, T. et al. (2019). iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network. Sci Rep 9, 11591. https://www.nature.com/articles/s41598-019-48004-8

[4] https://www.fiercebiotech.com/medtech/philips-gets-fda-nod-for-radiology-informatics-platform

[5] Nagpal, K., Foote, D., Liu, Y. (2019). Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer. npj Digit Med 2:48 https://www.nature.com/articles/s41746-019-0112-2

[6] The National Academies of Science Engineering Medicine (2015). Improving diagnosis in health care.https://www.ncbi.nlm.nih.gov/books/NBK338596/

[7] McKinney, S.M., Sieniek, M., Godbole, V. et al. (2020) International evaluation of an AI system for breast cancer screening. Nature 577, 89–94 https://pubmed.ncbi.nlm.nih.gov/31894144/

[8] Obuchowski, N.A., Bullen, J.A. (2019). Statistical considerations for testing an AI algorithm used for prescreening lung CT images. Contemporary Clinical Trials Communications 16:100434https://www.sciencedirect.com/science/article/pii/S2451865419301966

[9] Eykholt, K., Evtimov, I., Fernandes, E., et al. (2018) Robust physical-world attacks on deep learning models.arXiv preprint arXiv:1707.08945 https://arxiv.org/abs/1707.08945

[10] Van Hartskamp, M., Consoli, S., Verhaegh, W., Petkovic, M., Van de Stolpe, A. (2019). Artificial Intelligence in clinical healthcare applications: viewpoint. Interact J Med Res, 8(2): e12100.https://pubmed.ncbi.nlm.nih.gov/30950806/