June 06, 2026 preprint Open access Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders bioRxiv (Cold Spring Harbor Laboratory) DOI: 10.64898/2026.06.03.725182 Full text (OA) 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 Benchmarking foundation models as feature extractors for weakly supervised computational pathology 2025 Nature Biomedical Engineering article Computer Science AI in cancer detection Open access 73 citations Decoding pathology: the role of computational pathology in research and diagnostics 2024 Pflügers Archiv - European Journal of Physiology article Computer Science AI in cancer detection Open access 21 citations 2 results