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Research Data Analytics & AI
Knowing what the numbers will and will not support: design, analysis, interpretation, reproducibility, and where AI belongs in research work and where it does not. Everything here is free to read, written by the people who do the work, and revised when the standard underneath it moves. Where a sub-topic has nothing published under it yet, this page says so rather than listing a title that leads nowhere.
Each sub-topic below carries what is written, and names what is still being written.
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Everything in Research Data Analytics & AI
Sixteen items by sub-topic
Items may be browsed by sub-topic — study design, statistical analysis, interpreting results, evidence synthesis and reproducibility — or the whole category may be searched at once. Every item names the standard to which it is built and states whether it is currently available, and the filters allow further narrowing by item type and by the service the item supports.
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3WH Framework: Who, What, When, and How in a Research Question
A verified guide to the 3WH framework (What, Who, When, How) for structuring research questions, with a worked example and comparison to other non-PICO frameworks.
Posted 10 October 2026Reading time 7 minBy Pubrica Academy3WH frameworkresearch questionqualitative evidence synthesissearch strategyExampleResearch Data Analytics & AIPubrica AcademyAvailableA Critical Review of a Major Meta-Analysis on Physical Activity and Chronic Disease Risk
A verified critical review of Kyu and colleagues' 2016 BMJ meta-analysis on physical activity and chronic disease risk, covering its design strengths and its own stated limitations.
Posted 10 October 2026Reading time 9 minBy Pubrica Academymeta-analysis critiquephysical activitydose-responsechronic disease riskArticleResearch Data Analytics & AIYekaninejad et al., Obesity Reviews 2021AvailableA Meta-Analysis Evaluating the Prevalence of Food Addiction in Children and Adolescents
What a 2021 Obesity Reviews meta-analysis of 22 studies and 6,996 participants actually found about food addiction prevalence in children and adolescents, measured with the YFAS-C.
Posted 10 October 2026Reading time 6 minBy Pubrica Academyfood addictionYFAS-Cprevalencechildren adolescentsmeta-analysisConceptResearch Data Analytics & AIPubrica AcademyAvailableA Practical Guide to Confidence Intervals in Meta-Analysis
A practical, verified guide to how confidence intervals are built in meta-analysis, covering sampling error, between-study heterogeneity, and how to read them on a forest plot.
Posted 10 October 2026Reading time 8 minBy Pubrica Academyconfidence intervalmeta-analysisforest plotheterogeneityArticleResearch Data Analytics & AIPubrica AcademyAvailableA Primer on Decision Analysis for Clinical Investigators
A primer on clinical decision analysis for investigators — how decision trees and sensitivity analysis structure treatment choices under uncertainty and incorporate patient preference.
Posted 10 October 2026Reading time 7 minBy Pubrica Academyclinical decision analysisdecision treesensitivity analysisclinical epidemiologyArticleResearch Data Analytics & AIPubrica AcademyAvailableA Step-by-Step Workflow for Developing a Systematic Review Search Strategy
A verified, stage-by-stage workflow for developing a systematic review search strategy, from concept identification through database selection, Boolean combination, and validation.
Posted 10 October 2026Reading time 9 minBy Pubrica Academysearch strategy developmentsystematic reviewPRISMA-Sliterature search workflowArticleResearch Data Analytics & AIFrontiers in Plant Science, 2022AvailableA Systematic Review and Meta-Analysis of Plant Cell Technology for Production of Natural-Based Drugs
A verified comparison of paclitaxel production routes — bark extraction, semi-synthesis, total synthesis, and elicited plant cell culture — with the real reported yield figures.
Posted 10 October 2026Reading time 7 minBy Pubrica Academyplant cell culturepaclitaxel productionnatural product drugssystematic review biotechnologyArticleResearch Data Analytics & AIPubrica AcademyAvailableA Systematic Review of Machine Learning Methods for Predicting Cardiovascular Disease
A verified look at a 2025 systematic review comparing machine learning and deep learning methods for predicting cardiovascular disease, including screening methodology and reported performance figures.
Posted 10 October 2026Reading time 7 minBy Pubrica Academymachine learningcardiovascular diseasesystematic reviewdeep learningArticleResearch Data Analytics & AIEdwards & Aronson (2000) LancetAvailableAdverse Drug Effects: Definition and Classification
The precise difference between an adverse event and an adverse drug reaction, the standard mechanistic classification, and why causality has to be…
Posted 10 October 2026Reading time 8 minBy Pubrica Academyadverse drug reactionadverse eventpharmacovigilancedrug safetycausality assessmentADR classificationConceptResearch Data Analytics & AIICH E2A GuidelineAvailableAdverse Event, Serious Adverse Event and Adverse Drug Reaction: Why the Distinctions Decide What Must Be Reported, and How Fast
The ICH E2A definitions of adverse event, serious adverse event and adverse drug reaction, the specific seriousness criteria involved, and what combination of seriousness and causality triggers expedited regulatory reporting.
Posted 10 October 2026Reading time 6 minBy Pubrica Academyadverse eventserious adverse eventadverse drug reactionSUSARpharmacovigilanceICH E2AShelved by what each item is rather than what it is about: templates, guidelines, process flow charts and the twelve free tools each have a shelf of their own. To search across all four categories at once rather than this one, open the Academy library.
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While this category is in preparation, the tools that perform these calculations are already published and display their method alongside each result.
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The four categories follow the stages of the work itself: writing, interpretation, publication and dissemination.
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Scoping assessment and topic suggestions
A scoping assessment is provided free of charge within two business days. Readers may also suggest topics for coverage; most published items originated in reader requests.