Can ChatGPT write a good boolean query for systematic review literature search?

S Wang, H Scells, B Koopman, G Zuccon - Proceedings of the 46th …, 2023 - dl.acm.org
Systematic reviews are comprehensive literature reviews for a highly focused research
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 …

Medical concept normalization in clinical trials with drug and disease representation learning

Z Miftahutdinov, A Kadurin, R Kudrin… - …, 2021 - academic.oup.com
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 …

Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge

G Holste, Y Zhou, S Wang, A Jaiswal, M Lin… - Medical Image …, 2024 - Elsevier
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 …

RummaGEO: automatic mining of human and mouse gene sets from GEO

GB Marino, DJB Clarke, A Lachmann, EZ Deng… - Patterns, 2024 - cell.com
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 …

Dygen: Learning from noisy labels via dynamics-enhanced generative modeling

Y Zhuang, Y Yu, L Kong, X Chen, C Zhang - Proceedings of the 29th …, 2023 - dl.acm.org
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 …

BioSift: A Dataset for Filtering Biomedical Abstracts for Drug Repurposing and Clinical Meta-Analysis

D Kartchner, I Al-Hussaini, H Turner, J Deng… - Proceedings of the 46th …, 2023 - dl.acm.org
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 …

BioVAE: a pre-trained latent variable language model for biomedical text mining

HL Trieu, M Miwa, S Ananiadou - Bioinformatics, 2022 - academic.oup.com
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 …

Evaluating Large Language Models in Echocardiography Reporting: Opportunities and Challenges

CJ Chao, I Banerjee, R Arsanjani, C Ayoub, A Tseng… - medRxiv, 2024 - medrxiv.org
Background The increasing need for diagnostic echocardiography (echo) tests presents
challenges in preserving the quality and promptness of reports. While Large Language …

Continual knowledge infusion into pre-trained biomedical language models

K Jha, A Zhang - Bioinformatics, 2022 - academic.oup.com
Motivation Biomedical language models produce meaningful concept representations that
are useful for a variety of biomedical natural language processing (bioNLP) applications …