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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
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Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
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Related Experiment Video

Updated: Jun 11, 2025

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[Utilizing ChatGPT in Systematic Reviews and Meta-Analyses].

Hsiu-Min Chen1

  • 1PhD, Executive Director, Medata Statistic Consultant, Ltd., Taiwan, ROC. cshowme@gmail.com.

Hu Li Za Zhi the Journal of Nursing
|October 1, 2024
PubMed
Summary

ChatGPT can aid systematic reviews (SRs) and meta-analyses (MAs) in tasks like literature screening. However, human oversight is crucial for complex assessments due to AI limitations and potential errors.

Keywords:
ChatGPThuman-AI collaborationmeta-analysispractical recommendationssystematic review

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Area of Science:

  • Artificial Intelligence in Research
  • Evidence Synthesis Methodologies

Context:

  • Growing integration of AI tools in scientific research.
  • Need for guidelines on using AI in systematic reviews (SRs) and meta-analyses (MAs).

Purpose:

  • To review current uses, risks, and recommendations for ChatGPT in SRs and MAs.
  • To provide strategies for effective human-AI collaboration in evidence synthesis.

Summary:

  • ChatGPT shows promise in literature screening and data extraction for SRs/MAs.
  • AI performance is limited in complex tasks like risk of bias assessment, requiring human expertise.
  • Mitigating AI 'hallucinations' necessitates strict quality control and validation mechanisms.

Impact:

  • Enhancing efficiency in SRs and MAs through optimized human-AI collaboration.
  • Upholding scientific rigor and research integrity through transparency and ethical AI use.
  • Empowering researchers with prompt engineering and critical thinking skills for AI integration.