6 papers
Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons
Wei Tang, Jinpei Han, Kangning Cui +10
Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a range of clinical applications.…
Evaluating Computational Pathology Foundation Models for Prostate Cancer Grading under Distribution Shifts
Fredrik K. Gustafsson, Mattias Rantalainen
Pathology foundation models (PFMs) have emerged as powerful pretrained encoders for computational pathology, but their robustness under clinically relevant distribution shifts rema…
Benchmarking Pathology Foundation Models for Breast Cancer Survival Prediction
Fredrik K. Gustafsson, Constance Boissin, Johan Vallon-Christersson +2
Pathology foundation models (PFMs) have recently emerged as powerful pretrained encoders for computational pathology, enabling transfer learning across a wide range of downstream t…
Entropy Alone is Insufficient for Safe Selective Prediction in LLMs
Edward Phillips, Fredrik K. Gustafsson, Sean Wu +2
Selective prediction systems can mitigate harms resulting from language model hallucinations by abstaining from answering in high-risk cases. Uncertainty quantification techniques…
SignalMC-MED: A Multimodal Benchmark for Evaluating Biosignal Foundation Models on Single-Lead ECG and PPG
Fredrik K. Gustafsson, Xiao Gu, Mattia Carletti +3
Recent biosignal foundation models (FMs) have demonstrated promising performance across diverse clinical prediction tasks, yet systematic evaluation on long-duration multimodal dat…
Scanner-Induced Domain Shifts Undermine the Robustness of Pathology Foundation Models
Erik Thiringer, Fredrik K. Gustafsson, Kajsa Ledesma Eriksson +1
Pathology foundation models (PFMs) have become central to computational pathology, aiming to offer general encoders for feature extraction from whole-slide images (WSIs). Despite s…