2 papers
cs.CL2025
Cognitive bias in LLM reasoning compromises interpretation of clinical oncology notes
Matthew W. Kenaston, Umair Ayub, Mihir Parmar +14
Despite high performance on clinical benchmarks, large language models may reach correct conclusions through faulty reasoning, a failure mode with safety implications for oncology…
eess.IV2024
Fluoroformer: Scaling multiple instance learning to multiplexed images via attention-based channel fusion
Marc Harary, Eliezer M. Van Allen, William Lotter
Though multiple instance learning (MIL) has been a foundational strategy in computational pathology for processing whole slide images (WSIs), current approaches are designed for tr…