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Gudhe, N.R., Kosma, VM., Behravan, H. et al. Nuclei instance segmentation from histopathology images using Bayesian dropout based deep learning. BMC Med Imaging 23, 162 (2023). https://doi.org/10.1186/s12880-023-01121-3
R. Gudhe, H. Behravan, M. Sudah, V.-M Kosmaa, and A. Mannermaa. “Predicting cell type counts in whole slide histology images using evidential multi-task learning”. SPIE Medical Imaging, (2023).
Gudhe, N.R., Behravan, H., Sudah, M. et al. Area-based breast percentage density estimation in mammograms using weight-adaptive multitask learning. Sci Rep 12, 12060 (2022). https://doi.org/10.1038/s41598-022-16141-2
Gudhe, N.R., Behravan, H., Sudah, M. et al. Multi-level dilated residual network for biomedical image segmentation. Sci Rep 11, 14105 (2021). https://doi.org/10.1038/s41598-021-93169-w
Behravan, H., Hartikainen, J.M., Tengström, M. et al. Predicting breast cancer risk using interacting genetic and demographic factors and machine learning. Sci Rep 10, 11044 (2020). https://doi.org/10.1038/s41598-020-66907-9
Behravan, H., Hartikainen, J.M., Tengström, M. et al. Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controls. Sci Rep 8, 13149 (2018). https://doi.org/10.1038/s41598-018-31573-5
If you are interested in a project related to cancer risk and patient outcome prediction, you can consider reaching out to us.
University of Eastern Finland, Institute of Clinical Medicine
Yliopistonranta 1 C, Canthia building, Kuopio, Finland
hamid.behravan[@]uef.fi
+358 50 5139836
Copyright 2023 – Hamid Behravan
