AI Medical Compendium Topic

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MEDLINE

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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...

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...

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...

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 ...

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...

A High Recall Classifier for Selecting Articles for MEDLINE Indexing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
MEDLINE is the National Library of Medicine's premier bibliographic database for biomedical literature. A highly valuable feature of the database is that each record is manually indexed with a controlled vocabulary called MeSH. Most MEDLINE journals ...

Mining the literature for genes associated with placenta-mediated maternal diseases.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Automated literature analysis could significantly speed up understanding of the role of the placenta and the impact of its development and functions on the health of the mother and the child. To facilitate automatic extraction of information about pl...

Knowledge Extraction from MEDLINE by Combining Clustering with Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The identification of relevant predicates between co-occurring concepts in scientific literature databases like MEDLINE is crucial for using these sources for knowledge extraction, in order to obtain meaningful biomedical predications as subject-pred...

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease.

American journal of human genetics
The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been ava...