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Found 5 papers, 1 papers with code
MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation
Curated datasets for healthcare are often limited due to the need of human annotations from experts.
Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models
Medical image classification is a critical problem for healthcare, with the potential to alleviate the workload of doctors and facilitate diagnoses of patients.
"Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion
Based on our analysis, we define a disambiguation rewriting task to regenerate an input to be unambiguous while preserving information about the original content.
Weakly Supervised Contrastive Learning for Chest X-Ray Report Generation
Radiology report generation aims at generating descriptive text from radiology images automatically, which may present an opportunity to improve radiology reporting and interpretation.
Learning Visual-Semantic Embeddings for Reporting Abnormal Findings on Chest X-rays
In this work, we focus on reporting abnormal findings on radiology images; instead of training on complete radiology reports, we propose a method to identify abnormal findings from the reports in addition to grouping them with unsupervised clustering and minimal rules.
