Abstract The concept of Big Data is popular in a variety of domains. The purpose of this
review was to summarize the features, applications, analysis approaches, and challenges of …

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 …

Abstract Machine Learning (ML) studies algorithms which can learn from data to gain
knowledge from experience and to make decisions and predictions. Health Informatics (HI) …

We present a system for data‐driven therapy decision support based on techniques from the
field of recommender systems. Two methods for therapy recommendation, namely …

Biomedical experts are confronted with” Big data”, driven by the trend towards precision
medicine. Despite the fact that humans are excellent at pattern recognition in dimensions …

This work targets the development of a neighborhood-based Collaborative Filtering therapy
recommender system for clinical decision support. The proposed algorithm estimates …

The need of smart information retrieval systems is in contrast with the difficulties to deal with
huge amount of data. In this paper we present a Big Data Analytics architecture used to …

The exponential growth of healthcare data poses significant challenges for clinical
researchers who strive to identify meaningful patterns and correlations. The complexity of …

Healthcare is one of the core areas in medical domain. In healthcare the data exist in
various forms like respiration data, blood pressure readings, prescriptions and others. The …

A patient's estimated glomerular filtration rate (eGFR) can provide important information
about disease progression and kidney function. Traditionally, an eGFR time series is …