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  1. 2201
    “…The most common curriculum topics across the environmental scan and scoping review included AI fundamentals, applications of AI, applied machine learning in health care, ethics, data science, and challenges to and opportunities for using AI. …”
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    Accelerating the Appropriate Adoption of Artificial Intelligence in Health Care: Protocol for a Multistepped Approach
  2. 2202
    “…CONCLUSIONS: Our results highlight the clinical value of kinematic data collected during unsupervised goal-oriented motor training with the RGS combined with data science techniques, and provide new insight into factors underlying recovery and its biomarkers.…”
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    Estimating upper-extremity function from kinematics in stroke patients following goal-oriented computer-based training
  3. 2203
    “…The objective of this study is to assess various data science and machine learning techniques and determine their efficacy in forecasting mental health (MH) conditions among active duty Service Members (SMs) following a first diagnosis of mild traumatic brain injury (mTBI). …”
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    Evaluation of Machine Learning Techniques to Predict the Likelihood of Mental Health Conditions Following a First mTBI
  4. 2204
    “…Software for Statistics and Data Science (STATA) version 14 statistical software was used for the analysis. …”
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    Online Artículo Texto
    Prevalence and drug resistance patterns of Gram-negative enteric bacterial pathogens from diarrheic patients in Ethiopia: A systematic review and meta-analysis
  5. 2205
    “…Additional support was provided by CCSG Bioinformatics Shared Resource 5 (P30 CA046592), a gift from Agilent Technologies, a Research Scholar Grant from the American Cancer Society (RSG-16-005-01), a Precision Health Investigator Award from University of Michigan (U-M) Precision Health, the NCI (R37-CA214955), startup institutional research funds from U-M, and a Biomedical Informatics & Data Science Training Grant (T32GM141746).…”
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    Online Artículo Texto
    Central nervous system immune interactome is a function of cancer lineage, tumor microenvironment, and STAT3 expression
  6. 2206
    “…BACKGROUND: Personalized feedback is an effective behavior change technique frequently incorporated into mobile health (mHealth) apps. Innovations in data science create opportunities for leveraging the wealth of user data accumulated by mHealth apps to generate personalized health forecasts. …”
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    Online Artículo Texto
    Effects of a Novel Blood Glucose Forecasting Feature on Glycemic Management and Logging in Adults With Type 2 Diabetes Using One Drop: Retrospective Cohort Study
  7. 2207
    “…An interdisciplinary approach is essential, as data science, artificial intelligence, and engineering concepts (digital twins) can identify key risk factors throughout the life course, potentially enabling personalized simulation of life-course risk for the development of multimorbidity. …”
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    Life Course Digital Twins–Intelligent Monitoring for Early and Continuous Intervention and Prevention (LifeTIME): Proposal for a Retrospective Cohort Study
  8. 2208
    “…MATERIALS AND METHODS: Physicians, computer scientists and data science analysts participated in the development. …”
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    Online Artículo Texto
    Developing a real-world database for oncology: a descriptive analysis of breast cancer in Argentina
  9. 2209
    “…IMPORTANCE: Novel data science and marketing methods of smoking-cessation intervention have not been adequately evaluated. …”
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    Online Artículo Texto
    Effect of a Machine Learning Recommender System and Viral Peer Marketing Intervention on Smoking Cessation: A Randomized Clinical Trial
  10. 2210
    “…IBM SPSS Statistics 21 software and SPSSAU, a web-based data science algorithm platform tool, were used for all additional studies. …”
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    Development, validation and psychometric evaluation of the Chinese version of the biopsychosocial impact scale in orofacial pain patients
  11. 2211
    “…Such efforts will increase the reliability of findings and set the stage for more widespread applications of data science methods to these texts. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40621-023-00433-w.…”
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    Research utility and limitations of textual data in the National Violent Death Reporting System: a scoping review and recommendations
  12. 2212
    “…RESULTS: Of the 366 respondents to the survey, most worked in public health, data science, epidemiology, or business intelligence. …”
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    Influence of SARS-CoV-2 surveillance outputs produced by the UK health security agency (UKHSA) outbreak surveillance team on decision-making by local stakeholders
  13. 2213
    “…All studies presented MDSs with limitations or restrictions because they covered only a specific RD, or their scope of application was restricted to a specific context or geographic region. Data science methods and clinical experience were used to design, structure, and recommend a fundamental global MDS for RD patient records in health care networks. …”
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    The Minimum Data Set for Rare Diseases: Systematic Review
  14. 2214
    “…A new ontology of DHTs, combined with rigorous data science methods like those described in this paper, can be used to provide better information across the industry, and in turn, help create a more sustainable and equitable clinical trials enterprise. …”
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    Digital Health Technologies in Clinical Trials: An Ontology-Driven Analysis to Inform Digital Sustainability Policies
  15. 2215
    “…This area of research is inherently interdisciplinary, and this study supports this movement by applying public health, health communication, and data science approaches to extend methodologies across fields.…”
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    Online Artículo Texto
    Applying Multiple Data Collection Tools to Quantify Human Papillomavirus Vaccine Communication on Twitter
  16. 2216
    “…BACKGROUND: Pythia is an automated, clinically curated surgical data pipeline and repository housing all surgical patient electronic health record (EHR) data from a large, quaternary, multisite health institute for data science initiatives. In an effort to better identify high-risk surgical patients from complex data, a machine learning project trained on Pythia was built to predict postoperative complication risk. …”
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    Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study
  17. 2217
    “…H.R. is supported by the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center and by a research grant from Madame Olga Klein – Astrachan.…”
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    A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys
  18. 2218
    “…FUNDING: Global Financing Facility for Women, Children, and Adolescents Trust Fund; Development and Data Science grant; and the Yemen Emergency Health and Nutrition Project, a partnership between the World Bank, UNICEF, and WHO.…”
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    Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis
  19. 2219
    “…By capturing curators’ critical appraisal methodologies through the discrete labeling and rating of information, REDASA rapidly developed a foundational, pooled, data science data set of over 1400 articles in under 2 weeks. …”
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    Using a Secure, Continually Updating, Web Source Processing Pipeline to Support the Real-Time Data Synthesis and Analysis of Scientific Literature: Development and Validation Study
  20. 2220
    “…Greater data quality via digital form completion not only helps with auditing, service improvement, and patient record keeping but also helps with novel data science and machine learning research. Although digital forms are becoming more prevalent in health care, there is a lack of empirical best practices and guidelines for their design. …”
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    Comparing Single-Page, Multipage, and Conversational Digital Forms in Health Care: Usability Study
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