AIMC Topic: Semantics

Clear Filters Showing 1261 to 1270 of 1465 articles

The case for expressing nursing theories using ontologies.

Journal of the American Medical Informatics Association : JAMIA
Nursing and informatics share a common strength in their use of structured representations of domains, specifically the underlying notion of 'things' (ie, concepts, constructs, or named entities) and the relationships among those things. Accurate rep...

HTCL-DDI: a hierarchical triple-view contrastive learning framework for drug-drug interaction prediction.

Briefings in bioinformatics
Drug-drug interaction (DDI) prediction can discover potential risks of drug combinations in advance by detecting drug pairs that are likely to interact with each other, sparking an increasing demand for computational methods of DDI prediction. Howeve...

Few-shot biomedical named entity recognition via knowledge-guided instance generation and prompt contrastive learning.

Bioinformatics (Oxford, England)
MOTIVATION: Few-shot learning that can effectively perform named entity recognition in low-resource scenarios has raised growing attention, but it has not been widely studied yet in the biomedical field. In contrast to high-resource domains, biomedic...

DKADE: a novel framework based on deep learning and knowledge graph for identifying adverse drug events and related medications.

Briefings in bioinformatics
Adverse drug events (ADEs) are common in clinical practice and can cause significant harm to patients and increase resource use. Natural language processing (NLP) has been applied to automate ADE detection, but NLP systems become less adaptable when ...

Phen2Disease: a phenotype-driven model for disease and gene prioritization by bidirectional maximum matching semantic similarities.

Briefings in bioinformatics
Human Phenotype Ontology (HPO)-based approaches have gained popularity in recent times as a tool for genomic diagnostics of rare diseases. However, these approaches do not make full use of the available information on disease and patient phenotypes. ...

A Comparative Study of Deep Learning Methods for Multi-Class Semantic Segmentation of 2D Kidney Ultrasound Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Ultrasound (US) imaging is a widely used medical imaging modality for the diagnosis, monitoring, and surgical planning for kidney conditions. Thus, accurate segmentation of the kidney and internal structures in US images is essential for the assessme...

Learning Representations from Medical Text for Effective Diagnoses and Knowledge Discovery.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Discovering knowledge and effectively predicting target events are two main goals of medical text mining. However, few models can achieve them simultaneously. In this study, we investigated the possibility of discovering knowledge and predicting diag...

DEPAS: De-novo Pathology Semantic Masks using a Generative Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The integration of artificial intelligence (AI) into digital pathology has the potential to automate and improve various tasks, such as image analysis and diagnostic decision-making. Yet, the inherent variability of tissues, together with the need fo...

Assistive Completion of Agrammatic Aphasic Sentences: Amalgamation of NLP and Neurolinguistics-based Synthetic Dataset.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Damage to the inferior frontal gyrus (Broca's area) can cause agrammatic aphasia wherein patients, although able to comprehend, lack the ability to form complete sentences. This inability leads to communication gaps which cause difficulties in their ...

quEHRy: a question answering system to query electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).