Genomics & Precision Health Database| the Genomics & Health Impact Weekly Scan|PHGKB

Genomics & Precision Health Database| the Genomics & Health Impact Weekly Scan|PHGKB

Last Update Date: Aug 24, 2019

Non-Genomics Precision Health Update

The latest information and publications on the impact of big data science, machine learning and predictive analytics on public health.

• AI And Healthcare: Is The Bloom Finally Off The Rose
  D Shaywitz, Forbes, August 23, 2019
• Warning signs: Can data from mobile phones anticipate a suicide attempt?
  K Servick, Science, August 23, 2019
• Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning
  MP Ewbank et al, JAMA Psychiatry, August 22, 2019
• Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise.
  Xu Fengrui et al. JCO clinical cancer informatics 2019 Aug 31-15
• Research on Artificial Intelligence and Primary Care: A Scoping Review
  J Kueper et al, MexRXIV, AUgust 21, 2019
• Translating clinical trial results into personalized recommendations by considering multiple outcomes and subjective views
  N Dagan et al, NPJ Digital Medicine, August 21, 2019
• Warning of an AI winter, a skeptic argues deep learning in medicine needs a reboot
  C Ross, StatNews, August 21, 2019
• Whole-body magnetic resonance imaging (WB-MRI) in oncology: recommendations and key uses.
  Petralia Giuseppe et al. La Radiologia medica 2019 Mar 124(3) 218-233
• Social media captures demographic and regional physical activity.
  Cesare Nina et al. BMJ open sport & exercise medicine 2019 5(1) e000567
• Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative.
  Nellåker Christoffer et al. Frontiers in genetics 2019 10611
• Dual-Energy CT Texture Analysis With Machine Learning for the Evaluation and Characterization of Cervical Lymphadenopathy.
  Seidler Matthew et al. Computational and structural biotechnology journal 2019 171009-1015
• Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations.
  Kedra Joanna et al. RMD open 2019 5(2) e001004
• Artificial Intelligence for Surveillance in Public Health.
  Thiébaut Rodolphe et al. Yearbook of medical informatics 2019 Aug 28(1) 232-234
• Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility.
  Warner Jeremy L et al. Yearbook of medical informatics 2019 Aug 28(1) 236-238
• Clinical Research Informatics: Contributions from 2018.
  Daniel Christel et al. Yearbook of medical informatics 2019 Aug 28(1) 203-205
• Personalized Medicine Implementation with Non-traditional Data Sources: A Conceptual Framework and Survey of the Literature.
  Taylor Casey Overby et al. Yearbook of medical informatics 2019 Aug 28(1) 181-189
• Formal Medical Knowledge Representation Supports Deep Learning Algorithms, Bioinformatics Pipelines, Genomics Data Analysis, and Big Data Processes.
  Dhombres Ferdinand et al. Yearbook of medical informatics 2019 Aug 28(1) 152-155
• Contributions on Clinical Decision Support from the 2018 Literature.
  Koutkias Vassilis et al. Yearbook of medical informatics 2019 Aug 28(1) 135-137
• Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data.
  Conway Mike et al. Yearbook of medical informatics 2019 Aug 28(1) 208-217
• Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology.
  Rodríguez-González Alejandro et al. Yearbook of medical informatics 2019 Aug 28(1) 224-231

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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.