# Named Entities in Medical Case Reports: Corpus and Experiments

arXiv: https://arxiv.org/abs/2003.13032 · HTML: https://mlsanity.com/paper/2003.13032/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Mar 2020.

## Built on by (most cited first, 2 of 2)

- [PMC-Patients: A Large-scale Dataset of Patient Summaries and Relations for Benchmarking Retrieval-based Clinical Decision Support Systems](https://mlsanity.com/paper/2202.13876/) (2022)
- [MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI Applications with Retrieval Augmented Generation and Knowledge Graphs](https://mlsanity.com/paper/2407.02994/) (2024)

## Abstract (arXiv)

We present a new corpus comprising annotations of medical entities in case reports, originating from PubMed Central's open access library. In the case reports, we annotate cases, conditions, findings, factors and negation modifiers. Moreover, where applicable, we annotate relations between these entities. As such, this is the first corpus of this kind made available to the scientific community in English. It enables the initial investigation of automatic information extraction from case reports through tasks like Named Entity Recognition, Relation Extraction and (sentence/paragraph) relevance detection. Additionally, we present four strong baseline systems for the detection of medical entities made available through the annotated dataset.