BMC Medical Research Methodology

Papers
(The H4-Index of BMC Medical Research Methodology is 36. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models: a guide for evaluating large-scale health interventions313
Conducting proportional meta-analysis in different types of systematic reviews: a guide for synthesisers of evidence283
IPDfromKM: reconstruct individual patient data from published Kaplan-Meier survival curves266
COSMIN Risk of Bias tool to assess the quality of studies on reliability or measurement error of outcome measurement instruments: a Delphi study254
Major adverse cardiovascular event definitions used in observational analysis of administrative databases: a systematic review170
Real-world data: a brief review of the methods, applications, challenges and opportunities134
Open science saves lives: lessons from the COVID-19 pandemic129
Mediation analysis methods used in observational research: a scoping review and recommendations121
COVID-19-related medical research: a meta-research and critical appraisal111
Sample size calculation for prevalence studies using Scalex and ScalaR calculators92
Managing overlap of primary study results across systematic reviews: practical considerations for authors of overviews of reviews88
Impact of the COVID-19 pandemic on publication dynamics and non-COVID-19 research production80
Most published meta-regression analyses based on aggregate data suffer from methodological pitfalls: a meta-epidemiological study75
Conceptualising natural and quasi experiments in public health68
Machine learning in medicine: a practical introduction to natural language processing68
A narrative review on the validity of electronic health record-based research in epidemiology65
Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review60
Using a distribution-based approach and systematic review methods to derive minimum clinically important differences59
Application of machine learning in predicting hospital readmissions: a scoping review of the literature58
Methodological guidance for the evaluation and updating of clinical prediction models: a systematic review57
Facilitating harmonized data quality assessments. A data quality framework for observational health research data collections with software implementations in R57
A scoping review of Q-methodology in healthcare research56
Comparison of six statistical methods for interrupted time series studies: empirical evaluation of 190 published series54
Quality assessment tools used in systematic reviews of in vitro studies: A systematic review53
Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review48
Epistemonikos: a comprehensive database of systematic reviews for health decision-making46
A roadmap to using randomization in clinical trials45
Developing a toolkit for increasing the participation of black, Asian and minority ethnic communities in health and social care research45
Estimating age-specific COVID-19 fatality risk and time to death by comparing population diagnosis and death patterns: Australian data41
TIDieR-telehealth: precision in reporting of telehealth interventions used in clinical trials - unique considerations for the Template for the Intervention Description and Replication (TIDieR) checkli39
Re-evaluation of the comparative effectiveness of bootstrap-based optimism correction methods in the development of multivariable clinical prediction models39
A comparative study on deep learning models for text classification of unstructured medical notes with various levels of class imbalance38
Guidance for using artificial intelligence for title and abstract screening while conducting knowledge syntheses38
The unintended consequences of COVID-19 mitigation measures matter: practical guidance for investigating them37
Survival prediction models since liver transplantation - comparisons between Cox models and machine learning techniques37
Standardizing registry data to the OMOP Common Data Model: experience from three pulmonary hypertension databases36
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