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141. Semi-Automated Identification of Biomedical Literature | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/semi-automated-identification-biomedical-literature
     January 01, 2023 - Project Dates 09/30/2019 - 09/29/2020 Technology Artificial Intelligence Machine Learning … For this study, the research team used machine learning technologies, including natural language processing … represent the text of the citations in a form that can be used by information-retrieval and machine-learning … The system took as input a set of questions written in natural language and used a set of machine-learning … Document Type: Report Research Method: Algorithm Technology: Artificial Intelligence , Machine Learning

142. Intensive Care Unit | Digital Healthcare Research
     digital.ahrq.gov/care-setting/hospital-intensive-care-unit
     January 01, 2023 - Intensive Care Unit ML-ROVER: Machine Learning to Reduce Laboratory … Description The study will develop, validate, implement, and assess the usability of a machine learning … Principal Investigator(s) Kleinman, Keith Jeffers, Justin Machine Learning … Pharmacist Resource Prediction Description This research will develop and validate machine learning … Drug Event Prediction Description This research will use artificial intelligence and machine learning

143. Enabling Large-Scale Research on Autism Spectrum Disorders Through Automated Processing of EHR Using Natural Language Understanding - Final Report (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/r21hs024988-leroy-final-report-2020.pdf
     January 01, 2020 - Key Words: ASD, EHR, Natural Language Processing, NLP, machine learning, deep learning 2. … ) to tune deep learning hyper-parameters. … Leroy, “Use of Conventional Machine Learning to Optimize Deep Learning Hyper- parameters for NLP Labeling … Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research. 2012;12. 23. … Use of Conventional Machine Learning to Optimize Deep Learning Hyper- parameters for NLP Labeling Tasks

144. AHRQ National Webinar on Transforming Healthcare Through Patient-Generated Health Data Integration - Slides (pdf file)
     digital.ahrq.gov/sites/default/files/docs/pghd-slides-02222022.pdf
     February 22, 2022 - Learning Objectives At the conclusion of this webinar, participants should be able to: 1. … Assessing Readiness Key Learning Concepts • PGHD integration may mark a significant change in your … Active Learning Exercises • ACTIVITY 2.1: Organizational Readiness • ACTIVITY 2.2: Gauge Motivation … Active Learning Exercises • ACTIVITY 3.1: Identify Your Team of Champions • ACTIVITY 3.2: Assemble a … Making Decisions Key Learning Concepts • Identify information technology best suited to your PGHD

145. USA, MA, Boston | Digital Healthcare Research
     digital.ahrq.gov/location/usa-ma-boston
     January 01, 2023 - by using mixed methods (stakeholder interviews and surveys, electronic health records, and machine learning … Principal Investigator(s) Bates, David Rotenstein, Lisa Machine-Learning … Infection Care in Children Description The study will develop and implement a validated machine learning … Sepsis Phenotypes Associated with Antibiotic-Resistant Pathogens Using Large Language Models and Machine Learning … Description This research uses large language models and machine learning to retrospectively

146. Clinical Staff/Clinician | Digital Healthcare Research
     digital.ahrq.gov/population/clinical-staff
     January 01, 2024 - by using mixed methods (stakeholder interviews and surveys, electronic health records, and machine learning … HS030202 Principal Investigator(s) Abraham, Olufunmilola Machine-Learning … Infection Care in Children Description The study will develop and implement a validated machine learning … Principal Investigator(s) Wang, Hsin-Hsiao Scott ML-ROVER: Machine Learning … Description The study will develop, validate, implement, and assess the usability of a machine learning

147. Natural Language Processing System | Digital Healthcare Research
     digital.ahrq.gov/technology/natural-language-processing-system
     January 01, 2024 - Number R03 HS030307 Principal Investigator(s) Biro, Joshua A Machine Learning … A Machine Learning Health System to Integrate Care for Substance Misuse and HIV Treatment and Prevention … Project Name A Machine Learning Health System to Integrate Care for Substance Misuse and HIV Treatment … and Prevention Among Hospitalized Patients Automated, machine learning-based … Automated, machine learning-based alerts increase epilepsy surgery referrals: A randomized controlled

148. Pratap, Jayant | Digital Healthcare Research
     digital.ahrq.gov/principal-investigator/pratap-jayant
     January 01, 2023 - Pratap, Jayant Mining patient-specific and contextual data with machine learning … Mining patient-specific and contextual data with machine learning technologies to predict cancellation … Likely To Suffer Last-Minute Surgery Cancellation Description This research applied machine learning

149. A National Web Conference on Applying Advanced Analytics in Clinical Care: Slides (pdf file)
     digital.ahrq.gov/sites/default/files/docs/clinical-care-slides-10142020.pdf
     October 14, 2020 - Review how machine learning algorithms in conjunction with natural language processing can be used … Evaluate the benefits of using EHR-integrated machine learning algorithms to identify patients with … Describe how data mining and machine learning can help forecast adverse outcomes among surgical patients … "The learning healthcare system." (2007). … • We can improve pediatric care with unbiased machine learning algorithms • More opportunities for

150. Improving Missing Data Analysis in Distributed Research Networks | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/improving-missing-data-analysis-distributed-research-networks
     January 01, 2023 - Dates 09/30/2018 - 09/29/2022 Technology Artificial Intelligence Database Machine Learning … Aim 2: Apply and assess machine learning (ML) and predictive modeling techniques to address less-obvious … Document Type: Journal Publication Research Method: Algorithm , Quantitative Technology: Machine Learning … , Predictive Modeling Population: Researcher Applying machine learning in distributed data networks … Applying machine learning in distributed data networks for pharmacoepidemiologic and pharmacovigilance

151. USA, SC, Charleston | Digital Healthcare Research
     digital.ahrq.gov/location/usa-sc-charleston
     January 01, 2023 - Infrastructure to Create a Continuum of Services for COVID-19 Screening, Testing, and Treatment: A Learning … Rheingold, Alyssa Ann Learning From Primary Care EHR Exemplars About Health IT … R21 HS023863 Principal Investigator(s) Cartmell, Kathleen Buford Learning … Basco, William Research Centers in Primary Care Practice-Based Research and Learning

152. Pediatrics | Digital Healthcare Research
     digital.ahrq.gov/type-care/pediatrics
     January 01, 2023 - Machine-Learning Prediction Model for Personalized Urinary Tract Infection Care in Children Description … The study will develop and implement a validated machine learning model to optimize voiding cystourethrogram … Principal Investigator(s) Wang, Hsin-Hsiao Scott ML-ROVER: Machine Learning … Description The study will develop, validate, implement, and assess the usability of a machine learning … Asthma Treatment Response Description This research is developing and evaluating a machine learning

153. Using the Electronic Health Record To Identify Children Likely To Suffer Last-Minute Surgery Cancellation - Final Report (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/r21hs024983-pratap-final-report-2019.pdf
     January 01, 2019 - Machine learning classifiers were developed to predict all patient-related cancellations and the most … By learning from a set of training data, machine learning algorithms construct a predictive model to … The balanced data were then used to train the machine learning algorithms. … Performance of different machine learning classifiers for the Burnet campus dataset. … Performance of different machine learning classifiers for the Liberty campus dataset.

154. Improving Diagnosis and Treatment of Adult Depression Through Digital Healthcare Webinar: Slides (pdf file)
     digital.ahrq.gov/sites/default/files/docs/adult-depression-slides-06152022.pdf
     June 15, 2022 - • Questions will be read aloud by the moderator. 4 Learning Objectives At the conclusion of this … Carolyn Turvey, PhD carolyn-turvey@uiowa.edu 49 mailto:carolyn-turvey@uiowa.edu Reinforcement Learning … Machine Learning Supervised Machine Learning Unsupervised Machine Learning Reinforcement learning … Reinforcement Learning messages 2. Random messages 3. … Intervention Slide Number 64 Reinforcement Learning Important Terms The Reinforcement Learning Process

155. AHRQ Digital Healthcare Research Program - AT A Glance 2023 (pdf file)
     digital.ahrq.gov/sites/default/files/ahrq-dhr-2023-year-in-review-at-a-glance.pdf
     January 01, 2023 - Investigator(s) Type Improving Safety in Postoperative Handoff Communication with Telemedicine and Machine Learning … $1,996,227 Implementing a postoperative handoff interven- tion augmented with telemedicine and machine learning … McWilliams Carolinas Medical Center Completed Using Machine Learning for Military Service Members … Systems in Advancing Care Delivery Story Title Impact Statement Principal Investigator(s) Type Machine Learning … Research Investment: $1,952,312 The use of an emergency department triage tool informed by machine learning

156. Policy Relevant Evaluations to Inform Development of Health IT Meaningful Use Objectives (R18) | Digital Healthcare Research
     digital.ahrq.gov/funding-mechanism/policy-relevant-evaluations-inform-development-health-it-meaningful-use-objectives
     January 01, 2023 - Learning from primary care meaningful use exemplars. … Learning from primary care meaningful use exemplars. J Am Board Fam Med 2015;28(3):360-70. … Principal Investigator Ornstein, Steven Project Name Learning from Primary Care Meaningful … Principal Investigator Ornstein, Steven Project Name Learning from Primary Care Meaningful

157. Adverse Events | Digital Healthcare Research
     digital.ahrq.gov/health-care-theme/adverse-events
     January 01, 2023 - Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction … Description This research will develop and validate machine learning enhanced predictive models … Drug Event Prediction Description This research will use artificial intelligence and machine learning … Customizing Value-Based Methods to Prioritize Implementation of Pharmacogenomic Clinical Decision Support for Learning

158. Carroll, Aaron | Digital Healthcare Research
     digital.ahrq.gov/principal-investigator/carroll-aaron
     January 01, 2023 - Name Computer Automated Developmental Surveillance and Screening Machine learning … Machine learning techniques for prediction of early childhood obesity. … Patient-tailored prioritization for a pediatric care decision support system through machine learning … Patient-tailored prioritization for a pediatric care decision support system through machine learning

159. Wasserman, Richard | Digital Healthcare Research
     digital.ahrq.gov/principal-investigator/wasserman-richard
     January 01, 2023 - Richard National Center for Pediatric Practice Based Research and Learning … Wasserman, Richard Project Name National Center for Pediatric Practice-Based Research and Learning

160. Learning from Primary Care EHR Exemplars About HIT Safety - Final Report (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/r21hs024327-ornstein-final-report-2018.pdf
     January 01, 2018 - Learning from Primary Care EHR Exemplars About HIT Safety - Final Report Project Title … : Learning from Primary Care EHR E xemplars About HIT Safety Principal Investigator: Steven … Practices should consider joining a practice-based research or learning network to help them … Learning from Primary Care Meaningful Use Exemplars. … AHRQ Centers for Primary Care Practice-Based Research and Learning.