Resources
22 results for "reasoning"
Database
Contributor Review
ER-REASON: A Benchmark Dataset for LLM-Based Clinical Reasoning in the Emergency Room
The ER-Reason dataset is a benchmark designed to evaluate LLM-based clinical reasoning and decision-making in the emergency room (ER), a high-stakes setting where clinicians make rapid, consequential decisions across diverse patient presentations an…
Database
Credentialed Access
CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-rays
Recent progress in Large Vision-Language Models (LVLMs) has enabled promising applications in medical tasks such as report generation and visual question answering. However, existing benchmarks focus mainly on the final diagnostic answer, offering l…
Database
Credentialed Access
EHR-ReasonCon: Reasoning-Intensive Consistency Verification Between Clinical Notes and Structured Tables in Electronic Health Records
Electronic Health Records (EHRs) combine structured data, such as medications and laboratory measurements, with unstructured clinical notes describing patient conditions and clinical events. Although these two data types provide complementary inform…
Database
Credentialed Access
Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation
Radiology reports convey detailed clinical observations and capture diagnostic reasoning that evolves over time. However, existing evaluation methods are limited to single-report settings and rely on coarse metrics that fail to capture fine-grained …
fine-grained structured reports
attribute-level clinical reasoning
medical text structuring
longitudinal clinical reasoning
chest x-ray report parsing
medical information structuring
benchmark dataset for radiology report
medical information extraction
structured radiology reports
temporal relation extraction
radiology report benchmarking
longitudinal clinical understanding
Database
Restricted Access
MIMIC-IV-Ext-DiReCT
Large language models (LLMs) have recently demonstrated remarkable capabilities across a broad spectrum of tasks and applications, including the medical field. Models like GPT-4 excel in medical question answering but encounter challenges in interpr…
Database
Credentialed Access
MIMIC-IV-Ext-SDBench: Sequential Diagnosis Benchmark Cases Derived from MIMIC-IV
MIMIC-IV-Ext-SDBench contains 488 case records derived from MIMIC-IV emergency department encounters in which the patient was subsequently admitted as an inpatient. Each case is formatted primarily for use with the Sequential Diagnosis Benchmark, an…
Database
Credentialed Access
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images
Electronic Health Records (EHRs), which contain patients' medical histories in various multi-modal formats, often overlook the potential for joint reasoning across imaging and table modalities underexplored in current EHR Question Answering (QA) sys…
Database
Credentialed Access
Tasks 1 and 3 from Progress Note Understanding Suite of Tasks: SOAP Note Tagging and Problem List Summarization
Applying methods in natural language processing on electronic health records (EHR) data is a growing field. Existing corpus and annotation focus on modelling textual features and relation prediction [1] . However, there is a paucity of annotated cor…
Database
Credentialed Access
MIMIC-III-Ext-MIMIC-Patient: Structured Per-Patient JSON Records for Clinical Question Answering
This project provides MIMIC-Patient, a structured, per-patient representation of the MIMIC-III database designed for large language model (LLM)–based clinical question answering. For each of 500 admissions, we reconstruct the patient’s episode into …
Database
Credentialed Access
MIMIC-IV-Ext-MedicalBench: Evaluating Large Language Models Towards Improved Medical Concept Extraction
Medical concept extraction from electronic health records underpins many downstream applications, yet remains challenging because medically meaningful concepts, such as diagnosis, are frequently implied rather than explicitly stated in medical narra…