Researchers propose ReTA, a reinforcement learning-based dynamic topology augmentation framework that selectively imports external knowledge graph nodes and edges into electronic health record (EHR) v…
Researchers introduced ICD-Deepresearch, a DeepResearch workflow that combines structured EHR foundation models with language foundation models to forecast ICD codes for future clinical visits, achiev…
CoMedBench, a new benchmark introduced in arXiv:2608.12805v1, evaluates synthetic medical data fidelity and downstream utility across 37 dataset-task pairs from seven public sources, including MIMIC-I…
A new study from arXiv (2608.11410v1) introduces the Counterfactual Clinical Audit (CCA) framework, which stress-tests offline reinforcement learning (RL) agents for ICU sepsis management using physio…
Researchers propose MiGHT-EHR, a multi-task graph transformer for heterogeneous temporal electronic health records, which jointly models heterogeneous clinical entities, longitudinal patient trajector…
A new study from researchers evaluating large language models as unified multimodal learners for clinical prediction finds that converting all patient data into a single natural language sequence and …
Researchers used frozen medical large language model (LLM) representations to predict primary ICD categories from both clinical narratives and structured EHR data, achieving 87.69% strict accuracy on …
Researchers developed a diffusion-based model that generates irregular clinical time series by jointly modeling laboratory values and their observation patterns, using the MIMIC-III-derived DACMI benc…
A study published in JMIR Medical Informatics found that a three-pass large language model framework improved precision for radiology-report error detection, with positive predictive value rising from…