Data Science and Machine Learning in Public Health: Promises and Challenges C Patel et al, CDC Blog Post, September 20, 2019

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Last Posted: Sep 25, 2019

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• A quantitative approach for the analysis of clinician recognition of acute respiratory distress syndrome using electronic health record data.
  Bechel Meagan A et al. PloS one 2019 14(9) e0222826
• Data Science and Machine Learning in Public Health: Promises and Challenges
  C Patel et al, CDC Blog Post, September 20, 2019
• A Business Case for Artificial Intelligence Tools: The Currency of Improved Quality and Reduced Cost.
  Golding Lauren Parks et al. Journal of the American College of Radiology : JACR 2019 Sep 16(9 Pt B) 1357-1361
• Innovative Data Science to Transform Health Care: All the Pieces Matter.
  Masica Andrew L et al. EGEMS (Washington, DC) 2019 Aug 7(1) 47
• Towards Automating Location-Specific Opioid Toxicosurveillance from Twitter via Data Science Methods.
  Sarker Abeed et al. Studies in health technology and informatics 2019 Aug 264333-337
• Informatics and Data Science for the Precision in Symptom Self-Management Center.
  Bakken Suzanne et al. Studies in health technology and informatics 2019 Aug 2641827-1828
• Harnessing digital data and data science to achieve 90-90-90 goals to end the HIV epidemic.
  Strathdee Steffanie A et al. Current opinion in HIV and AIDS 2019 Aug
• Digital Phenotyping With Mobile and Wearable Devices: Advanced Symptom Measurement in Child and Adolescent Depression.
  Sequeira Lydia et al. Journal of the American Academy of Child and Adolescent Psychiatry 2019 Sep 58(9) 841-845
• In Pursuit of Evidence in Air Pollution Epidemiology: The Role of Causally Driven Data Science.
  Carone Marco et al. Epidemiology (Cambridge, Mass.) 2019 Aug
• How Big Data Science Can Improve Linkage and Retention in Care.
  Rana Aadia I et al. Infectious disease clinics of North America 2019 Sep 33(3) 807-815

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