Last Update Date: Oct 26, 2019
- Trends and Focus of Machine Learning Applications for Health Research
BB Jones et al, JAMA Network Open, October 25, 2019 - Trends and Focus of Machine Learning Applications for Health Research
BB Jones et al, JAMA Network Open, October 25, 2019 - Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer
RB Parikh et al, JAMA Network Open, October 25, 2019 - https://science.sciencemag.org/content/366/6464/447.full
Z Obermeyer et al, Science, October 25, 2019r - How the weather affects the pain of citizen scientists using a smartphone app
WG Dixon et al, NPJ digital Medicine, October 24, 2019 - Machine Learning for Suicide Research–Can It Improve Risk Factor Identification?
S Fazel et al, JAMA Psychiatry, October 23, 2019 - Translational AI and Deep Learning in Diagnostic Pathology.
Serag Ahmed et al. Frontiers in medicine 2019 6185 - Detecting the impact of subject characteristics on machine learning-based diagnostic applications.
Chaibub Neto Elias et al. NPJ digital medicine 2019 299 - Evaluation of Altered Functional Connections in Male Children With Autism Spectrum Disorders on Multiple-Site Data Optimized With Machine Learning.
Spera Giovanna et al. Frontiers in psychiatry 2019 10620 - On the Potential, Feasibility, and Effectiveness of Chat Bots in Public Health Research Going Forward.
Mierzwa Stanley et al. Online journal of public health informatics 2019 11(2) e4 - Machine Learning Predicts Accurately Mycobacterium tuberculosis Drug Resistance From Whole Genome Sequencing Data.
Deelder Wouter et al. Frontiers in genetics 2019 10922 - Deep Learning: A Review for the Radiation Oncologist.
Boldrini Luca et al. Frontiers in oncology 2019 9977 - Machine learning of human plasma lipidomes for obesity estimation in a large population cohort.
Gerl Mathias J et al. PLoS biology 2019 Oct 17(10) e3000443 - Predicting post-stroke pneumonia using deep neural network approaches.
Ge Yanqiu et al. International journal of medical informatics 2019 Oct 132103986 - Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things.
M Bublitz Frederico et al. International journal of environmental research and public health 2019 Oct 16(20) - A comparative study of machine learning classifiers for risk prediction of asthma disease.
Ullah Rahat et al. Photodiagnosis and photodynamic therapy 2019 Oct - Development and validation of an algorithm to assess risk of first-time falling among home care clients.
Kuspinar Ayse et al. BMC geriatrics 2019 Oct 19(1) 264 - Developing a FHIR-based EHR phenotyping framework: A case study for identification of patients with obesity and multiple comorbidities from discharge summaries.
Hong Na et al. Journal of biomedical informatics 2019 Oct 99103310 - Challenges to Transforming Unconventional Social Media Data into Actionable Knowledge for Public Health Systems During Disasters.
Chan Jennifer L et al. Disaster medicine and public health preparedness 2019 Oct 1-8 - MR-Forest: A Deep Decision Framework for False Positive Reduction in Pulmonary Nodule Detection.
Zhu Hongbo et al. IEEE journal of biomedical and health informatics 2019 Oct
Disclaimer: Articles listed in Non-Genomics Precision Health Update are selected by the CDC Office of Public Health Genomics 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.
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