Last Update Date: Jan 02, 2020
- Development and validation of a deep-learning model for scoring of radiographic finger joint destruction in rheumatoid arthritis.
Hirano Toru et al. Rheumatology advances in practice 2019 3(2) rkz047 - Applications of machine learning in decision analysis for dose management for dofetilide.
Levy Andrew E et al. PloS one 2019 14(12) e0227324 - Desiderata for delivering NLP to accelerate healthcare AI advancement and a Mayo Clinic NLP-as-a-service implementation.
Wen Andrew et al. NPJ digital medicine 2019 2130 - Preventing inpatient falls with injuries using integrative machine learning prediction: a cohort study.
Wang Lin et al. NPJ digital medicine 2019 2127 - Predicting breast cancer risk using personal health data and machine learning models.
Stark Gigi F et al. PloS one 2019 14(12) e0226765 - Study Progress of Radiomics With Machine Learning for Precision Medicine in Bladder Cancer Management.
Ge Lingling et al. Frontiers in oncology 2019 91296 - Mining the Thin Air-for Understanding of Urban Society.
Bekkerman Ron et al. Big data 2019 7(4) 262-275 - Opportunities for Artificial Intelligence in Advancing Precision Medicine.
Filipp Fabian V et al. Current genetic medicine reports 2019 Dec 7(4) 208-213 - Diagnostic accuracy of machine-learning-assisted detection for anterior cruciate ligament injury based on magnetic resonance imaging: Protocol for a systematic review and meta-analysis.
Lao Yongfeng et al. Medicine 2019 Dec 98(50) e18324 - Medical Big Data Is Not Yet Available: Why We Need Realism Rather than Exaggeration.
Kim Hun Sung et al. Endocrinology and metabolism (Seoul, Korea) 2019 Dec 34(4) 349-354 - Calibration and validation of accelerometry to measure physical activity in adult clinical groups: A systematic review.
Bianchim Mayara S et al. Preventive medicine reports 2019 Dec 16101001 - Deep Learning on Big, Sparse, Behavioral Data.
De Cnudde Sofie et al. Big data 2019 7(4) 286-307 - Breathing Signature as Vitality Score Index Created by Exercises of Qigong: Implications of Artificial Intelligence Tools Used in Traditional Chinese Medicine.
Zhang Junjie et al. Journal of functional morphology and kinesiology 2019 Dec 4(4) - [Digital Image Processing and Deep Neural Networks in Ophthalmology - Current Trends].
Bartschat Andreas et al. Klinische Monatsblatter fur Augenheilkunde 2019 Dec 236(12) 1399-1406 - Deep learning-based automated detection of retinal diseases using optical coherence tomography images.
Li Feng et al. Biomedical optics express 2019 Dec 10(12) 6204-6226 - Stratifying risk for dementia onset using large-scale electronic health record data: a retrospective cohort study.
McCoy Thomas H et al. Alzheimer's & dementia : the journal of the Alzheimer's Association 2019 Dec - Next Generation Clinical Practice - It's Man Versus Artificial Intelligence!
Bijarnia-Mahay Sunita et al. Indian pediatrics 2019 Dec 56(12) 1007-1008 - Predicting cognitive behavioral therapy outcome in the outpatient sector based on clinical routine data: A machine learning approach.
Hilbert Kevin et al. Behaviour research and therapy 2019 Dec 124103530 - Fundamentals in artificial intelligence for vascular surgeons.
Raffort Juliette et al. Annals of vascular surgery 2019 Dec - Pharmacoepidemiology and Big Data Analytics: Challenges and Opportunities when Moving towards Precision Medicine.
Burden Andrea M et al. Chimia 2019 Dec 73(12) 1012-1017
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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