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Found 9 papers, 6 papers with code
Towards Generalizable Methods for Automating Risk Score Calculation
Clinical risk scores enable clinicians to tabulate a set of patient data into simple scores to stratify patients into risk categories.
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
We conduct a human preference study on 100 CNN DailyMail articles and find that that humans prefer GPT-4 summaries that are more dense than those generated by a vanilla prompt and almost as dense as human written summaries.
Do We Still Need Clinical Language Models?
To investigate this question, we conduct an extensive empirical analysis of 12 language models, ranging from 220M to 175B parameters, measuring their performance on 3 different clinical tasks that test their ability to parse and reason over electronic health records.
Learning to Ask Like a Physician
The questions are generated by medical experts from 100+ MIMIC-III discharge summaries.
Does BERT Pretrained on Clinical Notes Reveal Sensitive Data?
The cost of training such models (and the necessity of data access to do so) coupled with their utility motivates parameter sharing, i. e., the release of pretrained models such as ClinicalBERT.
Understanding Clinical Trial Reports: Extracting Medical Entities and Their Relations
Here we consider the end-to-end task of both (a) extracting treatments and outcomes from full-text articles describing clinical trials (entity identification) and, (b) inferring the reported results for the former with respect to the latter (relation extraction).
Evidence Inference 2.0: More Data, Better Models
Ideally, we could consult a database of evidence gleaned from clinical trials to answer such questions.
ERASER: A Benchmark to Evaluate Rationalized NLP Models
We propose several metrics that aim to capture how well the rationales provided by models align with human rationales, and also how faithful these rationales are (i. e., the degree to which provided rationales influenced the corresponding predictions).
Inferring Which Medical Treatments Work from Reports of Clinical Trials
In this paper, we present a new task and corpus for making this unstructured evidence actionable.
