AIMC Topic: Abstracting and Indexing
Clear Filters Showing 41 to 50 of 51 articles
High-performance automated abstract screening with large language model ensembles.
Journal of the American Medical Informatics Association : JAMIA
May 1, 2025
OBJECTIVE: screening is a labor-intensive component of systematic review involving repetitive application of inclusion and exclusion criteria on a large volume of studies. We aimed to validate large language models (LLMs) used to automate abstract sc...
A question-answering framework for automated abstract screening using large language models.
Journal of the American Medical Informatics Association : JAMIA
Sep 1, 2024
OBJECTIVE: This paper aims to address the challenges in abstract screening within systematic reviews (SR) by leveraging the zero-shot capabilities of large language models (LLMs).
Characterizing the Increase in Artificial Intelligence Content Detection in Oncology Scientific Abstracts From 2021 to 2023.
JCO clinical cancer informatics
May 1, 2024
PURPOSE: Artificial intelligence (AI) models can generate scientific abstracts that are difficult to distinguish from the work of human authors. The use of AI in scientific writing and performance of AI detection tools are poorly characterized.
Affiliation Bias in Peer Review of Abstracts.
JAMA
Apr 9, 2024
Affiliation Bias in Peer Review of Abstracts-Reply.
JAMA
Apr 9, 2024
Publication Type Tagging using Transformer Models and Multi-Label Classification.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
Indexing articles by their publication type and study design is essential for efficient search and filtering of the biomedical literature, but is understudied compared to indexing by MeSH topical terms. In this study, we leveraged the human-curated p...
Supporting the use of standardized nursing terminologies with automatic subject heading prediction: a comparison of sentence-level text classification methods.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2020
OBJECTIVE: This study focuses on the task of automatically assigning standardized (topical) subject headings to free-text sentences in clinical nursing notes. The underlying motivation is to support nurses when they document patient care by developin...
Deep Learning and Online Video: Advances in Transcription, Automated Indexing, and Manipulation.
Medical reference services quarterly
Jan 1, 2018
In recent years, the amount of video content created and uploaded to the Internet has grown exponentially. Video content has unique accessibility challenges: indexing, transcribing, and searching video has always been very labor intensive, and there ...
Extracting Dependence Relations from Unstructured Medical Text.
Studies in health technology and informatics
Jan 1, 2015
Dependence relations among disease and risk factors are a key ingredient in risk modeling and decision support models. Currently such information is either provided by experts (costly and time consuming) or extracted from data (if available). The pub...
Identifying Clinical Study Types from PubMed Metadata: The Active (Machine) Learning Approach.
Studies in health technology and informatics
Jan 1, 2015
We examined a process for automating the classification of articles in MEDLINE aimed at minimising manual effort without sacrificing accuracy. From 22,808 articles pertaining to 19 antidepressants, 1000 were randomly selected and manually labelled ac...
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