Background Information technology has shifted paper-based documentation in the health
care sector into a digital form, in which patient information is transferred electronically from …

Natural products (NPs) are primarily recognized as privileged structures to interact with
protein drug targets. Their unique characteristics and structural diversity continue to marvel …

Traditional machine learning methods face unique challenges when applied to healthcare
predictive analytics. The high-dimensional nature of healthcare data necessitates labor …

Medical knowledge graphs (MKGs) are the basis for intelligent health care, and they have
been in use in a variety of intelligent medical applications. Thus, understanding the research …

With the growth of data and intelligent technologies, the healthcare sector opened numerous
technology that enabled services for patients, clinicians, and researchers. One major hurdle …

To provide accurate and explainable misinformation detection, it is often useful to take an
auxiliary source (eg, social context and knowledge base) into consideration. Existing …

Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Highlights•Biochemical data can be represented with text-based languages codified by
humans.•Natural language processing (NLP) can be applied to textual biochemical …

Knowledge Graph (KG) errors introduce non-negligible noise, severely affecting KG-related
downstream tasks. Detecting errors in KGs is challenging since the patterns of errors are …

Most of the existing medicine recommendation systems that are mainly based on electronic
medical records (EMRs) are significantly assisting doctors to make better clinical decisions …