Machine learning (ML) has been slowly entering every aspect of our lives and its positive
impact has been astonishing. To accelerate embedding ML in more applications and …

BACKGROUND Machine learning (ML) is a domain of artificial intelligence that allows
computer algorithms to learn from experience without being explicitly programmed …

Highlights•Big data has affected several sectors including biomedicine, life sciences and
scientific research.•Genetics and genomics information are key enablers for predictive and …

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self‐
reported pain level assessment has several limitations. Data‐driven artificial intelligence (AI) …

Current models for correlating electronic medical records with-omics data largely ignore
clinical text, which is an important source of phenotype information for patients with cancer …

Motivation The biomedical community's collective understanding of how chemicals, genes
and phenotypes interact is distributed across the text of over 24 million research articles …

Objective We implement 2 different multitask learning (MTL) techniques, hard parameter
sharing and cross-stitch, to train a word-level convolutional neural network (CNN) …

Abstract The National Center for Biomedical Ontology is now in its seventh year. The goals
of this National Center for Biomedical Computing are to: create and maintain a repository of …

Background Natural language processing (NLP) applications are increasingly important in
biomedical data analysis, knowledge engineering, and decision support. Concept …

Rapid growth of building components in the BIM object database increases the difficulty of
the efficient query of components that users require. Retrieval technology such as Autodesk …