Skip directly to search Skip directly to A to Z list Skip directly to navigation Skip directly to page options Skip directly to site content

Hot Topics of the Day|PHGKB
Search PHGKB:

10/21/2019

Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

Sign up MyPHGKB to receive the daily hot topic email alert.

Search Archive:
Archived Hot Topics of the Day By Date

Looking back and thinking forwards - 15 years of cardiology and cardiovascular research.
Kalman Jonathan M et al. Nature reviews. Cardiology 2019 Sep

Several practice-changing breakthroughs are described, such as those that target risk factors such as inflammation and elevated LDL-cholesterol levels. Furthermore, these key opinion leaders predict that machine learning technology and data derived from wearable devices will pave the way towards the coveted goal of personalized medicine.

The Colorectal Cancer Risk Assessment Tool
NCI, 2019 Brand

The Colorectal Cancer Risk Assessment Tool was designed for doctors and other health care providers to use with their patients. The tool estimates the risk of colorectal cancer over the next 5 years and the lifetime risk for men and women who are: Between the ages of 45 and 85. This tool takes about 5 minutes to complete.

NIH’s All of Us Partners with HudsonAlpha on Long-Read Sequencing Project
Clinical Omics, October 18, 2019

The NIH’s All of Us Research Program will assess the use of DNA sequencing technologies for diagnosis and treatment of common and rare diseases. The project will use long-read whole genome sequencing technologies to generate genetic data on about 6,000 samples from participants of different backgrounds.

Precision screening for familial hypercholesterolaemia: a machine learning study applied to electronic health encounter data
K Myers, Lancet Digital Health, October 21, 2019

The FIND FH model successfully scans large, diverse, and disparate health-care encounter databases to identify individuals with familial hypercholesterolemia. Using a machine learning model,we flagged 1?331?759 of 170?416?201 patients in the national database and 866 of 173?733 individuals in the health-care delivery system dataset as likely to have FH.


Disclaimer: Articles listed in Hot Topics of the Day are selected by Public Health Genomics Branch to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.
TOP