March 12, 2026 conference-paper Multi-Modal Deep Learning Framework for Endometrial Cancer Classification IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) DOI: 10.1109/iatmsi68868.2026.11465699 OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 0 References 2 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts 2022 The Lancet Digital Health article Computer Science AI in cancer detection Open access 134 citations Author Correction: Prediction of recurrence risk in endometrial cancer with multimodal deep learning 2024 Nature Medicine erratum Computer Science AI in cancer detection Open access 4 citations 2 results