Background: Natural Language Processing (NLP) methods are increasingly being utilized to
mine knowledge from unstructured health-related texts. Recent advances in noisy text …

Blockchain (BC) and artificial intelligence (AI) technologies have independent applications
in multiple industries, including banking, finance, healthcare, construction, transportation …

Research on extracting biomedical relations has received growing attention recently, with
numerous biological and clinical applications including those in pharmacogenomics, clinical …

Background We present a text-mining tool for recognizing biomedical entities in scientific
literature. OGER++ is a hybrid system for named entity recognition and concept recognition …

Background To detect attributes of medical concepts in clinical text, a traditional method
often consists of two steps: named entity recognition of attributes and then relation …

Objectives: To review the latest scientific challenges organized in clinical Natural Language
Processing (NLP) by highlighting the tasks, the most effective methodologies used, the data …

Heart disease is a leading cause of death worldwide. For decades, cardiologists have
attempted to identify heart-disease risk factors to facilitate its prediction, prevention, and …

Objective To solve major clinical natural language processing (NLP) tasks using a unified
text-to-text learning architecture based on a generative large language model (LLM) via …

Normalization maps clinical terms in medical notes to standardized medical vocabularies. In
order to capture semantic similarity between different surface expressions of the same …

State-of-the-art developments in multiple new technologies for older adult care Grounded in
a unique team-based geriatrics perspective, this book delivers a broad range of current …