Biomedical information extraction (BioIE) is an important task. The aim is to analyze
biomedical texts and extract structured information such as named entities and semantic …

Drug discovery and development is a complex and costly process. Machine learning
approaches are being investigated to help improve the effectiveness and speed of multiple …

Over the past couple of decades, the explosion of densely interconnected data has
stimulated the research, development and adoption of graph database technologies. From …

Biomedical research is growing at such an exponential pace that scientists, researchers,
and practitioners are no more able to cope with the amount of published literature in the …

Background Biomedical translational science is increasingly using computational reasoning
on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome …

Knowledge-based biomedical data science involves the design and implementation of
computer systems that act as if they knew about biomedicine. Such systems depend on …

Systemic analysis of available large-scale biological/biomedical data is critical for studying
biological mechanisms, and developing novel and effective treatment approaches against …

Human interaction in natural language with computer systems has been a prime focus of
research, and the field of conversational agents (including chatbots and Interactive Voice …

In the current practice, an essential element of safety management systems, Job Hazard
Analysis (JHA), is performed manually, relying on the safety personnel's experiential …

Animal parasitic diseases not only have an economic impact, but also have serious social
and public health impacts. Although antiparasitic drugs can treat these diseases, it seems …