Can ChatGPT write a good boolean query for systematic review literature search?
Systematic reviews are comprehensive literature reviews for a highly focused research
question. These reviews are considered the highest form of evidence in medicine. Complex …
question. These reviews are considered the highest form of evidence in medicine. Complex …
[HTML][HTML] Natural Language Processing in Medicine and Ophthalmology: A Review for the 21st-century clinician
W Rojas-Carabali, R Agrawal… - Asia-Pacific Journal of …, 2024 - Elsevier
ABSTRACT Natural Language Processing (NLP) is a subfield of artificial intelligence that
focuses on the interaction between computers and human language, enabling computers to …
focuses on the interaction between computers and human language, enabling computers to …
Medical concept normalization in clinical trials with drug and disease representation learning
Motivation Clinical trials are the essential stage of every drug development program for the
treatment to become available to patients. Despite the importance of well-structured clinical …
treatment to become available to patients. Despite the importance of well-structured clinical …
Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge
Many real-world image recognition problems, such as diagnostic medical imaging exams,
are “long-tailed”–there are a few common findings followed by many more relatively rare …
are “long-tailed”–there are a few common findings followed by many more relatively rare …
RummaGEO: automatic mining of human and mouse gene sets from GEO
Summary The Gene Expression Omnibus (GEO) has millions of samples from thousands of
studies. While users of GEO can search the metadata describing studies, there is a need for …
studies. While users of GEO can search the metadata describing studies, there is a need for …
Dygen: Learning from noisy labels via dynamics-enhanced generative modeling
Learning from noisy labels is a challenge that arises in many real-world applications where
training data can contain incorrect or corrupted labels. When fine-tuning language models …
training data can contain incorrect or corrupted labels. When fine-tuning language models …
BioSift: A Dataset for Filtering Biomedical Abstracts for Drug Repurposing and Clinical Meta-Analysis
This work presents a new, original document classification dataset, BioSift, to expedite the
initial selection and labeling of studies for drug repurposing. The dataset consists of 10,000 …
initial selection and labeling of studies for drug repurposing. The dataset consists of 10,000 …
BioVAE: a pre-trained latent variable language model for biomedical text mining
Large-scale pre-trained language models (PLMs) have advanced state-of-the-art (SOTA)
performance on various biomedical text mining tasks. The power of such PLMs can be …
performance on various biomedical text mining tasks. The power of such PLMs can be …
Evaluating Large Language Models in Echocardiography Reporting: Opportunities and Challenges
Background The increasing need for diagnostic echocardiography (echo) tests presents
challenges in preserving the quality and promptness of reports. While Large Language …
challenges in preserving the quality and promptness of reports. While Large Language …
Continual knowledge infusion into pre-trained biomedical language models
Motivation Biomedical language models produce meaningful concept representations that
are useful for a variety of biomedical natural language processing (bioNLP) applications …
are useful for a variety of biomedical natural language processing (bioNLP) applications …