OBJECTIVES: A common prerequisite for tasks such as classification, prediction, clustering and retrieval of longitudinal medical records is a clinically meaningful similarity measure that considers both [multiple] variable (concept) values and their ...
Anxiety disorders are common among youth, posing risks to physical and mental health development. Early screening can help identify such disorders and pave the way for preventative treatment. To this end, the Youth Online Diagnostic Assessment (YODA)...
Entity relation extraction plays an important role in the biomedical, healthcare, and clinical research areas. Recently, pre-trained models based on transformer architectures and their variants have shown remarkable performances in various natural la...
The effectiveness of machine learning models to provide accurate and consistent results in drug discovery and clinical decision support is strongly dependent on the quality of the data used. However, substantive amounts of open data that drive drug d...
When it comes to inferring relations between entities in biomedical texts, Relation Extraction (RE) has become key to biomedical information extraction. Although previous studies focused on using rule-based and machine learning-based approaches, thes...
OBJECTIVES: Biomedical natural language processing tools are increasingly being applied for broad-coverage information extraction-extracting medical information of all types in a scientific document or a clinical note. In such broad-coverage settings...
Interpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation of an attention layer for L...
BACKGROUND: Recent natural language processing (NLP) research is dominated by neural network methods that employ word embeddings as basic building blocks. Pre-training with neural methods that capture local and global distributional properties (e.g.,...
The analysis of human body composition plays a critical role in health management and disease prevention. However, current medical technologies to accurately assess body composition such as dual energy X-ray absorptiometry, computed tomography, and m...
In this paper, a novel approach is proposed for the analysis of time-course gene expression data based on the path-breaking work of Zadeh, Computing with Words. This method can automatically discover the patterns of temporal gene expression profile i...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.