Papers
Evaluation of Multi-Agent LLMs in Multidisciplinary Team Decision-Making for Challenging Cancer Cases
Jaesik Kim, Byounghan Lee, Kyung-Ah Sohn et al.
Optimizing Segmentation of Neonatal Brain MRIs with Partially Annotated Multi-Label Data
Dariia Kucheruk, Sam Osia, Pouria Mashouri et al.
Bidirectional Hierarchical Protein Multi-Modal Representation Learning
Xuefeng Liu, Songhao Jiang, Chih-chan Tien et al.
ScaffoldGPT: A Scaffold-based GPT Model for Drug Optimization
Xuefeng Liu, Songhao Jiang, Ian Foster et al.
Patient-Specific Deep Reinforcement Learning for Automatic Replanning in Head-and-Neck Cancer Proton Therapy
Malvern Madondo, Yuan Shao, Yingzi Liu et al.
FactEHR: A Dataset for Evaluating Factuality in Clinical Notes Using LLMs
Monica Munnangi, Akshay Swaminathan, Jason Alan Fries et al.
Improving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models
Anish Narain, Ritam Majumdar, Nikita Narayanan et al.
ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs
Fahmida Liza Piya, Rahmatollah Beheshti
Clinicians’ Voice: Fundamental Considerations for XAI in Healthcare
Tabea Elina Röber, Rob Goedhart, Ilker Birbil
Rare Disease Differential Diagnosis with Large Language Models at Scale: From Abdominal Actinomycosis to Wilson’s Disease
Elliot Schumacher, Dhruv Naik, Anitha Kannan
ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning
Sahil Sethi, David Chen, Thomas Statchen et al.
Stepwise Fine and Gray: Subject-Specific Variable Selection Shows When Hemodynamic Data Improves Prognostication of Comatose Post-Cardiac Arrest Patients
Xiaobin Shen, Jonathan Elmer, George H. Chen
Switching State Space Modeling via Constrained Inference for Clinical Outcome Prediction
Arnold Su, Anna Wong, Fareed Sheriff et al.
Borrowing From the Future: Enhancing Early Risk Assessment through Contrastive Learning
Minghui Sun, Matthew M. Engelhard, Benjamin Goldstein
Classifying Copy Number Variations Using State Space Modeling of Targeted Sequencing Data: A Case Study in Thalassemia
Austin Talbot, Alex V. Kotlar, Lavanya Rishishwar et al.
Biomedical Hypothesis Explainability with Graph-Based Context Retrieval
Ilya Tyagin, Saeideh Valipour, Aliaksandra Sikirzhytskaya et al.
FIVA: Federated Inverse Variance Averaging for Universal CT Segmentation with Uncertainty Estimation
Asim Ukaye, Numan Saeed, Karthik Nandakumar
Monte Carlo ExtremalMask: Uncertainty Aware Time Series Model Interpretability For Critical Care Applications
Shashank Yadav, Vignesh Subbian
The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA
Eric Yang, Jonathan Amar, Jong Ha Lee et al.
LEAVES: Learning Views for Time-Series Biobehavioral Data in Contrastive Learning
Han Yu, Huiyuan Yang, Akane Sano
TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction
Sihang Zeng, Lucas Jing Liu, Jun Wen et al.
INSIGHT: Explainable Weakly-Supervised Medical Image Analysis
Wenbo Zhang, Junyu Chen, Christopher Kanan
Balancing Interpretability and Flexibility in Modeling Diagnostic Trajectories with an Embedded Neural Hawkes Process Model
Yuankang Zhao, Matthew M. Engelhard
Your other Left! Vision-Language Models Fail to Identify Relative Positions in Medical Images
Daniel Wolf, Heiko Hillenhagen, Billurvan Taskin et al.