| # | Title | Journal | Year | Citations |
|---|
| 1 | Utilization of the PICO framework to improve searching PubMed for clinical questions | BMC Medical Informatics and Decision Making | 2007 | 1,667 |
| 2 | Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers | BMC Medical Informatics and Decision Making | 2008 | 966 |
| 3 | A Systematic Review of Healthcare Applications for Smartphones | BMC Medical Informatics and Decision Making | 2012 | 870 |
| 4 | Factors influencing the implementation of clinical guidelines for health care professionals: A systematic meta-review | BMC Medical Informatics and Decision Making | 2008 | 828 |
| 5 | Comparing different supervised machine learning algorithms for disease prediction | BMC Medical Informatics and Decision Making | 2019 | 716 |
| 6 | Cognitive biases associated with medical decisions: a systematic review | BMC Medical Informatics and Decision Making | 2016 | 574 |
| 7 | Explainability for artificial intelligence in healthcare: a multidisciplinary perspective | BMC Medical Informatics and Decision Making | 2020 | 503 |
| 8 | Predicting disease risks from highly imbalanced data using random forest | BMC Medical Informatics and Decision Making | 2011 | 462 |
| 9 | Smartphone and medical related App use among medical students and junior doctors in the United Kingdom (UK): a regional survey | BMC Medical Informatics and Decision Making | 2012 | 455 |
| 10 | Understanding factors affecting patient and public engagement and recruitment to digital health interventions: a systematic review of qualitative studies | BMC Medical Informatics and Decision Making | 2016 | 449 |
| 11 | The SAIL databank: linking multiple health and social care datasets | BMC Medical Informatics and Decision Making | 2009 | 442 |
| 12 | A systematic development process for patient decision aids | BMC Medical Informatics and Decision Making | 2013 | 391 |
| 13 | “Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice | BMC Medical Informatics and Decision Making | 2013 | 374 |
| 14 | Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers | BMC Medical Informatics and Decision Making | 2013 | 369 |
| 15 | Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system | BMC Medical Informatics and Decision Making | 2017 | 354 |
| 16 | Integrated Personal Health Records: Transformative Tools for Consumer-Centric Care | BMC Medical Informatics and Decision Making | 2008 | 352 |
| 17 | A clinical text classification paradigm using weak supervision and deep representation | BMC Medical Informatics and Decision Making | 2019 | 348 |
| 18 | Predicting sample size required for classification performance | BMC Medical Informatics and Decision Making | 2012 | 343 |
| 19 | Nearest neighbor imputation algorithms: a critical evaluation | BMC Medical Informatics and Decision Making | 2016 | 328 |
| 20 | Application of support vector machine modeling for prediction of common diseases: the case of diabetes and pre-diabetes | BMC Medical Informatics and Decision Making | 2010 | 318 |
| 21 | Adoption of telemedicine: from pilot stage to routine delivery | BMC Medical Informatics and Decision Making | 2012 | 313 |
| 22 | Extracting principal diagnosis, co-morbidity and smoking status for asthma research: evaluation of a natural language processing system | BMC Medical Informatics and Decision Making | 2006 | 299 |
| 23 | The GuideLine Implementability Appraisal (GLIA): development of an instrument to identify obstacles to guideline implementation | BMC Medical Informatics and Decision Making | 2005 | 283 |
| 24 | Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone | BMC Medical Informatics and Decision Making | 2020 | 282 |
| 25 | Development of a targeted client communication intervention to women using an electronic maternal and child health registry: a qualitative study | BMC Medical Informatics and Decision Making | 2020 | 278 |
| 26 | IT-adoption and the interaction of task, technology and individuals: a fit framework and a case study | BMC Medical Informatics and Decision Making | 2006 | 277 |
| 27 | Methods for identifying 30 chronic conditions: application to administrative data | BMC Medical Informatics and Decision Making | 2016 | 275 |
| 28 | Systematic review of prognostic models in traumatic brain injury | BMC Medical Informatics and Decision Making | 2006 | 273 |
| 29 | Automated de-identification of free-text medical records | BMC Medical Informatics and Decision Making | 2008 | 272 |
| 30 | The R0 package: a toolbox to estimate reproduction numbers for epidemic outbreaks | BMC Medical Informatics and Decision Making | 2012 | 262 |
| 31 | Appraisal of the Karnofsky Performance Status and proposal of a simple algorithmic system for its evaluation | BMC Medical Informatics and Decision Making | 2013 | 259 |
| 32 | The use of mobile phones as a data collection tool: A report from a household survey in South Africa | BMC Medical Informatics and Decision Making | 2009 | 258 |
| 33 | Privacy-preserving record linkage using Bloom filters | BMC Medical Informatics and Decision Making | 2009 | 243 |
| 34 | The role of artificial intelligence in healthcare: a structured literature review | BMC Medical Informatics and Decision Making | 2021 | 242 |
| 35 | How the public uses social media wechat to obtain health information in china: a survey study | BMC Medical Informatics and Decision Making | 2017 | 234 |
| 36 | Assessing the level of healthcare information technology adoption in the United States: a snapshot | BMC Medical Informatics and Decision Making | 2006 | 223 |
| 37 | Impact of unlinked deaths and coding changes on mortality trends in the Swiss National Cohort | BMC Medical Informatics and Decision Making | 2013 | 215 |
| 38 | A data-driven approach to predicting diabetes and cardiovascular disease with machine learning | BMC Medical Informatics and Decision Making | 2019 | 209 |
| 39 | Is the coverage of google scholar enough to be used alone for systematic reviews | BMC Medical Informatics and Decision Making | 2013 | 205 |
| 40 | Addressing health literacy in patient decision aids | BMC Medical Informatics and Decision Making | 2013 | 197 |
| 41 | Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare | BMC Medical Informatics and Decision Making | 2010 | 195 |
| 42 | Improving palliative care with deep learning | BMC Medical Informatics and Decision Making | 2018 | 194 |
| 43 | Time series modeling for syndromic surveillance | BMC Medical Informatics and Decision Making | 2003 | 192 |
| 44 | Patient-centered medicine and patient-oriented research: improving health outcomes for individual patients | BMC Medical Informatics and Decision Making | 2013 | 190 |
| 45 | Effective behavioral intervention strategies using mobile health applications for chronic disease management: a systematic review | BMC Medical Informatics and Decision Making | 2018 | 190 |
| 46 | Building the national health information infrastructure for personal health, health care services, public health, and research | BMC Medical Informatics and Decision Making | 2003 | 188 |
| 47 | Forty years of SNOMED: a literature review | BMC Medical Informatics and Decision Making | 2008 | 188 |
| 48 | Clarifying values: an updated review | BMC Medical Informatics and Decision Making | 2013 | 188 |
| 49 | Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital | BMC Medical Informatics and Decision Making | 2015 | 176 |
| 50 | Establishing the effectiveness of patient decision aids: key constructs and measurement instruments | BMC Medical Informatics and Decision Making | 2013 | 174 |
