AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

MEDLINE

Showing 1 to 10 of 48 articles

Clear Filters

Automatic MeSH Indexing: Revisiting the Subheading Attachment Problem.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This year less than 200 National Library of Medicine indexers expect to index 1 million articles, and this would not be possible without the assistance of the Medical Text Indexer (MTI) system. MTI is an automated indexing system that provides MeSH m...

Hybrid Ensemble-Rule Algorithm for Improved MEDLINE® Sentence Boundary Detection.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Sentence boundary detection (SBD) is a fundamental building block in the Natural Language Processing (NLP) pipeline. Incorrect SBD may impact subsequent processing stages resulting in decreased performance. In well-behaved corpora, a few simple rules...

Applying a novel approach to scoping review incorporating artificial intelligence: mapping the natural history of gonorrhoea.

BMC medical research methodology
BACKGROUND: Systematic and scoping literature searches are increasingly resource intensive. We present the results of a scoping review which combines the use of a novel artificial-intelligence-(AI)-assisted Medline search tool with two other 'traditi...

Machine learning algorithms to identify cluster randomized trials from MEDLINE and EMBASE.

Systematic reviews
BACKGROUND: Cluster randomized trials (CRTs) are becoming an increasingly important design. However, authors of CRTs do not always adhere to requirements to explicitly identify the design as cluster randomized in titles and abstracts, making retrieva...

Bat4RCT: A suite of benchmark data and baseline methods for text classification of randomized controlled trials.

PloS one
Randomized controlled trials (RCTs) play a major role in aiding biomedical research and practices. To inform this research, the demand for highly accurate retrieval of scientific articles on RCT research has grown in recent decades. However, correctl...

Classifying literature mentions of biological pathogens as experimentally studied using natural language processing.

Journal of biomedical semantics
BACKGROUND: Information pertaining to mechanisms, management and treatment of disease-causing pathogens including viruses and bacteria is readily available from research publications indexed in MEDLINE. However, identifying the literature that specif...

Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques.

Artificial intelligence in medicine
OBJECTIVE: The proper handling of missing values is critical to delivering reliable estimates and decisions, especially in high-stakes fields such as clinical research. In response to the increasing diversity and complexity of data, many researchers ...

Few-shot learning for medical text: A review of advances, trends, and opportunities.

Journal of biomedical informatics
BACKGROUND: Few-shot learning (FSL) is a class of machine learning methods that require small numbers of labeled instances for training. With many medical topics having limited annotated text-based data in practical settings, FSL-based natural langua...

Understanding the factors influencing acceptability of AI in medical imaging domains among healthcare professionals: A scoping review.

Artificial intelligence in medicine
BACKGROUND: Artificial intelligence (AI) technology has the potential to transform medical practice within the medical imaging industry and materially improve productivity and patient outcomes. However, low acceptability of AI as a digital healthcare...

Enhancing the coverage of SemRep using a relation classification approach.

Journal of biomedical informatics
OBJECTIVE: Relation extraction is an essential task in the field of biomedical literature mining and offers significant benefits for various downstream applications, including database curation, drug repurposing, and literature-based discovery. The b...