Kitamura, Felipe C.

Federated learning for predicting clinical outcomes in patients with COVID-19

Dayan, I., Roth, H. R., Zhong, A., Harouni, A., Gentili, A., Abidin, A. Z., Liu, A., Costa, A. B., Wood, B. J., Tsai, C.-S., et al. (2021) · Nature Medicine

Machine Learning in HealthcareCOVID-19 diagnosis using AI

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Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update

Tejani, A. S., Klontzas, M. E., Gatti, A. A., Mongan, J. T., Moy, L., Park, S. H., Kahn, C. E., Panel, F. T. C. 2. U., Abbara, S., Afat, S., et al. (2024) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationRadiomics and Machine Learning in Medical Imaging

Cited by 570

ChatGPT is shaping the future of medical writing but still requires human judgment

Kitamura, F. C. (2023) · Radiology

Artificial Intelligence in Healthcare and EducationAcademic Writing and Publishing

Cited by 317

Federated Learning for Breast Density Classification: A Real-World Implementation

Roth, H. R., Chang, K., Singh, P., Neumark, N., Li, W., Gupta, V., Gupta, S., Qu, L., Ihsani, A., Bizzo, B. C., et al. (2020) · Lecture Notes in Computer Science

Privacy-Preserving Technologies in DataAI in cancer detection

Cited by 202

Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients

Busch, F., Hoffmann, L., Xu, L., Zhang, L. J., Hu, B., García-Juárez, I., Toapanta-Yanchapaxi, L. N., Gorelik, N., Gorelik, V., Rodriguez-Granillo, G. A., et al. (2025) · JAMA Network Open

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 124

Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays

Gaube, S., Suresh, H., Raue, M., Lermer, E., Koch, T. K., Hudecek, M. F. C., Ackery, A. D., Grover, S. C., Coughlin, J. F., Frey, D., et al. (2023) · Scientific Reports

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 92

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

Mese, I., D’Antonoli, T. A., Bluethgen, C., Bressem, K., Cuocolo, R., Chaudhari, A., Tejani, A. S., Isaac, A., Ponsiglione, A., Meddeb, A., et al. (2026) · Diagnostic and Interventional Radiology

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

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Who should do as AI say? Only non-task expert physicians benefit from correct explainable AI advice

Gaube, S., Suresh, H., Raue, M., Lermer, E., Koch, T., Hudecek, M., Ackery, A. D., Grover, S. C., Coughlin, J. F., Frey, D., et al. (2022) · Research Square

Artificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)

Cited by 3