Machine Learning in Healthcare and Medicine

Displaying 1 - 6 of 6CSV
Mielke, M. M., Kurzman, H. R., Hu, Y. H., Cho, M., Liss, J., Burns, J. M., Obisesan, T. O., Hornbecker, M., Pallay, A., Smith, S. R., Honig, L. S., Parker, M. W., Bell, J., & Hampel, H. (2024). Advancing Early Detection of Alzheimer’s Disease in the Primary Care Setting in the United States. Alzheimer’s & Dementia, 20(S2). Portico. https://doi.org/10.1002/alz.086582
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Campbell, E. A., Bose, S., & Masino, A. J. (2024). Conceptualizing bias in EHR data: A case study in performance disparities by demographic subgroups for a pediatric obesity incidence classifier. PLOS Digital Health, 3(10), e0000642. https://doi.org/10.1371/journal.pdig.0000642
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Wu, Y., Zhuo, C., Lu, Y., Luo, Z., Lu, L., Wang, J., Tang, Q., Phipps, M. M., Nahm, W. J., Facciorusso, A., & Ge, B. (2024). A machine learning clinic scoring system for hepatocellular carcinoma based on the Surveillance, Epidemiology, and End Results database. Journal of Gastrointestinal Oncology, 15(3), 1082–1100. https://doi.org/10.21037/jgo-24-230
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Parikh, S. A., & Monteleone, P. (2024). LB-6 | Disparities in Pulmonary Embolism Care: Insights from Big Data Analytics. Journal of the Society for Cardiovascular Angiography & Interventions, 3(5), 101875. https://doi.org/10.1016/j.jscai.2024.101875
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Reyes‐Dumeyer, D., Piriz, A., Soriano, B., Franco, Y., Coronado, Z. D., Recio, P., Mejia, D. R., Medrano, M., Lantigua, R. A., Vardarajan, B. N., Honig, L. S., & Mayeux, R. (2023). Biomarker collection from the Caribbean Hispanic families from Dominican Republic and New York. Alzheimer’s & Dementia, 19(S22). Portico. https://doi.org/10.1002/alz.074856
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Wang, K., Shi, Q., Sun, C., Liu, W., Yau, V., Xu, C., Liu, H., Sun, C., Yin, C., Wei, X., Li, W., & Rong, L. (2023). A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study. Frontiers in Neuroscience, 17. https://doi.org/10.3389/fnins.2023.1130831
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