For medical imaging, and related clinical co-variables, you can find various datasets here:
Furthermore, some of our works [1, 2, 3] have a deep comprehension of these datasets published in peer-review journals and conferences. Our work aims at developing a database for a complete set of clinical attributes to train Artificial Intelligence (AI) models. These AI models are trained under supervised information provided by clinicians from several medical institutions.
 Francisco M. Calisto, Alfredo Ferreira, Jacinto C. Nascimento, and Daniel Gonçalves. 2017. Towards Touch-Based Medical Image Diagnosis Annotation. In Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces (ISS '17). Association for Computing Machinery, New York, NY, USA, 390–395. DOI: https://doi.org/10.1145/3132272.3134111
 Francisco Maria Calisto, Nuno Nunes, and Jacinto C. Nascimento. 2020. BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis. In Proceedings of the International Conference on Advanced Visual Interfaces (AVI '20). Association for Computing Machinery, New York, NY, USA, Article 49, 1–5. DOI: https://doi.org/10.1145/3399715.3399744
 Francisco Maria Calisto, Carlos Santiago, Nuno Nunes, Jacinto C. Nascimento, Introduction of human-centric AI assistant to aid radiologists for multimodal breast image classification, International Journal of Human-Computer Studies, Volume 150, 2021, 102607, ISSN 1071-5819, DOI: https://doi.org/10.1016/j.ijhcs.2021.102607