Resources

9 results for "natural language inference"

Database Credentialed Access

RadNLI: A natural language inference dataset for the radiology domain

Yasuhide Miura, Yuhao Zhang, Emily Tsai, et al.

The problem of natural language inference (NLI) determines whether a natural language hypothesis can be justifiably inferred from a natural language premise. NLI has attracted researchers to benchmark it in a number of settings including medical one…
Published: June 29, 2021. Version: 1.0.0
Database Credentialed Access

RuMedNLI: A Russian Natural Language Inference Dataset For The Clinical Domain

Pavel Blinov, Aleksandr Nesterov, Galina Zubkova, et al.

There is a shortage of text medical resources for the Russian language. This is a substantial obstacle in state-of-the-art NLP deep learning models research and development. To mitigate this issue we translated the MedNLI data from English to Russia…
Published: April 1, 2022. Version: 1.0.0
Database Credentialed Access

MedNLI - A Natural Language Inference Dataset For The Clinical Domain

Chaitanya Shivade

State of the art models using deep neural networks have become very good in learning an accurate mapping from inputs to outputs. However, they still lack generalization capabilities in conditions that differ from the ones encountered during training…
Published: Oct. 1, 2019. Version: 1.0.0
Database Credentialed Access

CORAL: expert-Curated medical Oncology Reports to Advance Language model inference

Madhumita Sushil, Vanessa Kennedy, Divneet Mandair, et al.

Both medical care and observational studies in oncology require a thorough understanding of a patient's disease progression and treatment history, often elaborately documented within clinical notes. As large language models (LLMs) are becoming more …
Published: Feb. 7, 2024. Version: 1.0
Database Credentialed Access

MedNLI for Shared Task at ACL BioNLP 2019

Chaitanya Shivade

Natural Language Inference (NLI) is the task of determining whether a given hypothesis can be inferred from a given premise. Also known as Recognizing Textual Entailment (RTE), this task has enjoyed popularity among researchers for some time. Howeve…
Published: Nov. 28, 2019. Version: 1.0.1
Model Credentialed Access

Fine-tuning foundational models to code diagnoses from veterinary health records

Adam Kiehl, Nadia Saklou, G Joseph Strecker, et al.

Veterinary medical records represent a large data resource for application to veterinary and One Health clinical research efforts. Use of the data is limited by interoperability challenges including inconsistent data formats and data siloing. Clinic…
Published: Jan. 25, 2026. Version: 1.0.0
Database Credentialed Access

Tasks 1 and 3 from Progress Note Understanding Suite of Tasks: SOAP Note Tagging and Problem List Summarization

Yanjun Gao, John Caskey, Timothy Miller, et al.

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…
Published: Sept. 30, 2022. Version: 1.0.0
Database Credentialed Access

Phenotype Annotations for Patient Notes in the MIMIC-III Database

Edward Moseley, Leo Anthony Celi, Joy Wu, et al.

A crucial step within secondary analysis of electronic health records (EHRs) is to identify the patient cohort under investigation. While EHRs contain medical billing codes that aim to represent the conditions and treatments patients may have, much …
Published: March 5, 2020. Version: 1.20.3
Database Restricted Access

CXRGraph: Using Information Extraction to Normalize the Training Data for Automatic Radiology Report Generation

Yuxiang Liao, Hoisang Heung, Hantao Liu, et al.

CXRGraph is a dataset of structured radiology reports dataset following the RadGraph format, which has been tailored for the Automatic Radiology Report Generation (ARRG) task. CXRGraph assorts clinical information from full-text radiology reports in…
Published: Feb. 3, 2025. Version: 1.0.0