Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

Background: Novel approaches that complement and go beyond evidence-based medicine
are required in the domain of chronic diseases, given the growing incidence of such …

Imaging research laboratories are rapidly creating machine learning systems that achieve
expert human performance using open-source methods and tools. These artificial …

Heterogeneity in sepsis and acute respiratory distress syndrome (ARDS) is increasingly
being recognized as one of the principal barriers to finding efficacious targeted therapies …

Objective Electronic health records (EHRs) are a promising source of data for health
outcomes research in oncology. A challenge in using EHR data is that selecting cohorts of …

TG is a shareholder of Westlake Omics Inc. TI is a cofounder of Data4Cure, is on the
Scientific Advisory Board and has an equity interest. TI is on the Scientific Advisory Board of …

Objective To discover diverse genotype-phenotype associations affiliated with Type 2
Diabetes Mellitus (T2DM) via genome-wide association study (GWAS) and phenome-wide …

The potential for big data analytics to improve cardiovascular quality of care and patient
outcomes is tremendous. However, the application of big data in health care is at a nascent …

Objective Health care generated data have become an important source for clinical and
genomic research. Often, investigators create and iteratively refine phenotype algorithms to …

The wide adoption of electronic health record systems in health care generates big real-
world data that open new venues to conduct clinical research. As a large amount of valuable …