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  1. digital.ahrq.gov/organization/george-washington-university
    January 01, 2023 - Integrity Description This research will develop and validate advanced statistical and machine learning
  2. digital.ahrq.gov/principal-investigator/nelson-stuart-james
    January 01, 2023 - Integrity Description This research will develop and validate advanced statistical and machine learning
  3. digital.ahrq.gov/topics-az/m
    January 01, 2023 - M N P Q R S T U V W Machine Learning
  4. digital.ahrq.gov/care-setting/community-health-center
    January 01, 2023 - Community Health Center Machine-Learning Prediction Model for Personalized … Infection Care in Children Description The study will develop and implement a validated machine learning
  5. digital.ahrq.gov/principal-investigator/rangachari-pavani
    January 01, 2023 - Enable Meaningful Use of EHR Technology A qualitative study of interprofessional learning … A qualitative study of interprofessional learning related to electronic health record (EHR) medication
  6. digital.ahrq.gov/funding-mechanism/ahrq-small-research-grant-program-r03
    January 01, 2023 - A Longitudinal Machine Learning Approach Providing Clinicians Timely Detection to Prevent Military Suicide … Asthma Treatment Response Description This research is developing and evaluating a machine learning
  7. digital.ahrq.gov/organization/brigham-and-womens-hospital
    January 01, 2023 - by using mixed methods (stakeholder interviews and surveys, electronic health records, and machine learning … risk of death over the next 12 months and found it was better than benchmark statistical and machine learning
  8. digital.ahrq.gov/technology/data-warehouse
    January 01, 2023 - (EDM) Forum Second Phase Description The Electronic Data Methods (EDM) Forum facilitated learning … researchers and other key stakeholders who are generating the data, methods, and knowledge needed to build learning
  9. digital.ahrq.gov/funding-mechanism/centers-education-and-research-therapeutics-certs-u19
    January 01, 2023 - Project Name Tools for Optimizing Medication Safety (TOP-MEDS) LearningLearning from errors: analysis of medication order voiding in CPOE systems.
  10. digital.ahrq.gov/health-care-theme/us-preventive-services-task-force-recommendations
    January 01, 2023 - Sebastian, Sharon Quilty, Mary McCready, Robert A Longitudinal Machine Learning … Infrastructure Employing the USPSTF Recommendations in Computable Form Description This study used learning
  11. digital.ahrq.gov/2020-year-review/research-summary/using-natural-language-processing-improve-autism-spectrum-disorder-research-and-care
    January 01, 2020 - Natural language processing and other machine learning techniques convert unstructured text into structured … In addition, machine learning algorithms were used to label a child’s clinical record as either ASD or
  12. digital.ahrq.gov/health-care-theme/patient-centered-care
    January 01, 2023 - An Age-Friendly Learning Healthcare System: A Transformative Digital Solution for Geriatrics Clinics … Fraenkel, Liana A Longitudinal Machine Learning Approach Providing Clinicians
  13. digital.ahrq.gov/technology/imaging-system
    January 01, 2023 - Classification of diabetic retinopathy images using multi-class multiple-instance learning … Classification of diabetic retinopathy images using multi-class multiple-instance learning based on color
  14. digital.ahrq.gov/sites/default/files/docs/citation/r21hs022336-farris-final-report-2017.pdf
    January 01, 2017 - Learning by the RL agent was also seen, as the distribution of text messages changed over time. … Key Words: medication adherence; reinforcement learning; hypertension 2 … We propose to apply artificial intelligence (AI) methods, specifically Reinforcement Learning (one type … Demonstrate “learning” by the RL-based system through adaptation of the SMS message stream according … Demonstrate “learning” by the RL-based system through adaptation of the SMS message stream according
  15. digital.ahrq.gov/sites/default/files/docs/publication/r18hs018646-gance-cleveland-final-report-2014.pdf
    January 01, 2014 - Components of the web-based collaborative electronic learning community. … community Module C (variable) Implementing guidelines E-Learning community Chat room … community Module C (variable) Implementing guidelines E-Learning community Chat room … Completion rates of the first two learning sessions were much higher than the final two sessions. … Participant completion of training modules by content area and learning session.
  16. digital.ahrq.gov/organization/cleveland-clinic-foundation
    January 01, 2023 - Description This research will develop, validate, and evaluate a decision support tool using a machine learning
  17. digital.ahrq.gov/location/bloomington
    January 01, 2023 - Asthma Treatment Response Description This research is developing and evaluating a machine learning
  18. digital.ahrq.gov/principal-investigator/owora-arthur-hamie
    January 01, 2023 - Asthma Treatment Response Description This research is developing and evaluating a machine learning
  19. digital.ahrq.gov/organization/indiana-university
    January 01, 2023 - Asthma Treatment Response Description This research is developing and evaluating a machine learning
  20. digital.ahrq.gov/principal-investigator/butler-jorie-m
    January 01, 2023 - An Age-Friendly Learning Healthcare System: A Transformative Digital Solution for Geriatrics Clinics

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