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Updated: May 2, 2026

Gold Nanoparticle Synthesis

Gold Nanoparticle Synthesis

Published on: July 10, 2021

Refining gold from existing data.

¹National Jewish Health, Denver, Colorado, USA.

Current Opinion in Allergy and Clinical Immunology

|March 15, 2014

Summary

This summary is machine-generated.

Leveraging existing health data accelerates discovery and improves generalizability. While challenges exist, data reuse offers compelling benefits for research efficiency and real-world applicability.

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Millifluidics for Chemical Synthesis and Time-resolved Mechanistic Studies

Millifluidics for Chemical Synthesis and Time-resolved Mechanistic Studies

Published on: November 27, 2013

Area of Science:

Health Research
Data Science
Epidemiology

Background:

Growing emphasis on evidence-based practice and personalized medicine.
Increasing volume and complexity of health data generated.
Need for efficient and cost-effective research methodologies.

Purpose of the Study:

To review the arguments supporting the increased utilization of existing data in health research.
To explore the epistemological, economic, and efficiency-based justifications for data reuse.
To identify potential challenges associated with health data reuse.

Main Methods:

Literature review of arguments for data reuse.
Analysis of justifications including epistemological, cost, power, and efficiency.
Consideration of informatics, cultural, societal, and regulatory issues.

Main Results:

Data reuse is increasingly justified for observational, exploratory, and outcome studies.
Epistemological arguments highlight data reuse as a path to new knowledge and real-world generalizability.
Cost, power, and efficiency gains are significant, despite informatics, cultural, societal, and regulatory hurdles.

Conclusions:

Data reuse presents a compelling case for advancing health research.
Partnership with existing data holders should be considered for research plans outside of efficacy-focused Randomized Controlled Trials (RCTs).
Strategic integration of existing data is crucial for optimizing research outcomes.