The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …

The recent years have witnessed a surge of interests in data analytics with patient Electronic
Health Records (EHR). Data-driven healthcare, which aims at effective utilization of big …

To make predictions and explore large datasets, healthcare is increasingly applying
advanced algorithms of artificial intelligence. However, to make well‐considered and …

Temporal event sequence data is increasingly commonplace, with applications ranging from
electronic medical records to financial transactions to social media activity. Previously …

The rapid growth in the development of healthcare information systems has led to an
increased interest in utilizing the patient Electronic Health Records (EHR) for assisting …

We describe visual analytics solutions aiming to support public health professionals, and
thus, preventive measures. Prevention aims at advocating behaviour and policy changes …

Biomedical research is drowning in data, yet starving for knowledge. Current challenges in
biomedical research and clinical practice include information overload–the need to combine …

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve
clinical prediction tasks. Although many ML models perform promisingly, issues with model …

In recent decades, the bioinformatics, biology and biotechnology plays a major role in
accumulation of numerous biomedical data, which offers an in-depth analysis. On other …