Resources
17 results for "automatically generated dataset"
Database
Credentialed Access
RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
RadGraph is a dataset of entities and relations in full-text radiology reports. We designed a novel information extraction (IE) schema to structure clinical information in a radiology report with four entities and three relations. Our train set cons…
Database
Credentialed Access
ReEvalMed: Rethinking Medical Report Evaluation by Aligning Metrics with Real-World Clinical Judgment
Automatically generated radiology reports often receive high scores from existing evaluation metrics but fail to earn clinicians' trust. This gap reveals fundamental flaws in how current metrics assess the quality of generated reports. We rethink th…
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
CLIP: A Dataset for Extracting Action Items for Physicians from Hospital Discharge Notes
We created a dataset of clinical action items annotated over MIMIC-III. This dataset, which we call CLIP, is annotated by physicians and covers 718 discharge summaries, representing 107,494 sentences. Annotations were collected as character-level sp…
Challenge
Credentialed Access
BioNLP Workshop 2023 Shared Task 1A: Problem List Summarization
Automatically summarizing patients’ main problems from the daily care notes in the electronic health record can help mitigate information and cognitive overload for clinicians and provide augmented intelligence via computerized diagnostic decision s…
Database
Credentialed Access
MIMIC-III-Ext-VeriFact-BHC: Labeled Propositions From Brief Hospital Course Summaries for Long-form Clinical Text Evaluation
The VeriFact-BHC dataset is designed to verify the factuality of long-form text written about a patient against their own electronic health record. There is increasing interest in using large language models (LLMs) to generate clinical text in patie…
natural language processing
clinical informatics
formal logic
clinical notes
chart review
text embedding
brief hospital course
long-form text
logical atomism
retrieval-augmented generation
text reranking
clinical medicine
atomic claim
fact verification
hybrid retrieval
llm-as-a-judge
llm evaluation
electronic health records
large language models
artificial intelligence
Database
Credentialed Access
MIMIC-Ext-CXR-QBA: A Structured, Tagged, and Localized Visual Question Answering Dataset with Question-Box-Answer Triplets and Scene Graphs for Chest X-ray Images
Visual Question Answering (VQA) enables flexible and context-dependent analysis of medical images, such as chest X-rays (CXRs), by allowing users to pose specific questions and receive nuanced answers. However, existing CXR VQA datasets are typicall…