Machine learning (ML) has been slowly entering every aspect of our lives and its positive
impact has been astonishing. To accelerate embedding ML in more applications and …

Background Concept extraction, a subdomain of natural language processing (NLP) with a
focus on extracting concepts of interest, has been adopted to computationally extract clinical …

The widespread use of electronic health records (EHR) systems in health care provides a
large amount of real-world data, leading to new areas for clinical research. Natural language …

Background The medical subdomain of a clinical note, such as cardiology or neurology, is
useful content-derived metadata for developing machine learning downstream applications …

Rapid growth in electronic health records (EHRs) use has led to an unprecedented
expansion of available clinical data in electronic formats. However, much of the important …

With the completion of the Human Genome Project1 as well as recent advances in genomic
science and comparative biological studies, a new era of individualized medicine is evolving …

Electronic health record systems are ubiquitous and the majority of patients' data are now
being collected electronically in the form of free text. Deep learning has significantly …

Abstract The 2016 CEGS N-GRID shared tasks for clinical records contained three tracks.
Track 1 focused on de-identification of a new corpus of 1000 psychiatric intake records. This …

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

Big Data is, clearly, an integral part of modern information societies. A vast amount of data is
daily produced and it is estimated that, for the years to come, this number will grow …