YJiahui Geng, Ynli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan decker, Chunming Rong, Towards General Deep Leakage in Federated Learning, in the International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjunction with AAAI 2022 (FL-AAAI-22) 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021).įL-AAAI-22: International Workshop on Trustable, Verifiable and Auditable Federated Learning in Conjuction with AAAI 2022 (2 March- 2022 Online) Katsaggelos, Combining Attention-based Multiple Instance Learning and Gaussian Processes for CT Hemorrhage Detection. Yunan Wu, Arne Schmidt, Enrique Hernández Sánchez, Rafael Molina, and Aggelos K. MICCAI 2021: MICCAI 2021: International Conference on Medical Image Computingand Computer Assisted Intervention (27 Sep – Online) 4th Workshop on Parallel, Distributed and Federated Learning at ECML-PKDD 2021. Yongli Mou, Jiahui Geng, Sascha Welten, Chunming Rong, Stefan Decker, and Oya Beyan, Optimized Federated Learning on Class-biased Distributed Data Sources. Specific and challenging cancer types have been selected to test the tools and methods developed through the project reflecting the existing variability in cancer diagnosis: Triple negative breast cancer (TNBC), High-risk non-muscle invasive bladder cancer (HR-NMIBC) and Spitzoid melanocytic lesions (SML).ĮCML-PKDD 2021: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (13-17
CLARIFY is an innovative, multinational, multi-sectorial, and multidisciplinary research and training programme that links two highly differentiated specialities: engineering and medicine, to produce 12 Early Stage Researchers (ESRs) in artificial intelligence (AI), cloud computing and clinical pathology with the focus on digital pathology.ĬLARIFY’s main goal is to develop a robust automated digital diagnostic environment based on artificial intelligence and cloud-oriented data algorithms that facilitates whole-slide-image (WSI) interpretation and diagnosis everywhere with the aim of maximising the benefits of digital pathology and aiding pathologists in their daily work.ĬLARIFY gathers relevant scientific staff from academia, industry and leading hospitals ensuring that CLARIFY’s ESRs, as well as, future PhD students following the same tracks, will have outstanding Career Opportunities within the digital pathology sector and beyond.
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