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Mathematical modeling transforms real-world scenarios into mathematical expressions, allowing for structured problem-solving and analysis. This process involves defining the situation, assigning variables to measurable quantities, selecting an appropriate model, and solving the resulting equation. Such models are invaluable in finance, providing precise methods to evaluate investments, loans, and repayment structures.A widely used example is the calculation of fixed monthly payments on a loan,...
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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Related Experiment Video

Updated: Nov 23, 2025

Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training
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Mathematical models in nursing research.

Teresa Rea1, Assunta Guillari1, Consolato Sergi2

  • 1Department of Public Health, University Federico II of Naples, Italy.

Journal of Public Health Research
|December 31, 2020
PubMed
Summary
This summary is machine-generated.

Advanced mathematical models are increasingly used in nursing research, driven by artificial intelligence and Big Data. Collaboration between nurses and mathematicians can enhance research and improve patient care outcomes.

Keywords:
Big DataNurseartificial neural networksmathematical modelsnursing researchnursing toolsquestionnaires

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Area of Science:

  • Nursing Research
  • Mathematical Modeling
  • Health Informatics

Background:

  • Mathematical models are established in medical research for predictive analysis, such as experimental tumor growth.
  • Historically, the application of advanced mathematical tools in nursing research has been limited.
  • Recent advancements in artificial intelligence (AI) and Big Data have spurred increased adoption of these methods in nursing.

Purpose of the Study:

  • To highlight the growing importance and benefits of advanced mathematical tools in nursing research.
  • To emphasize the need for interdisciplinary collaboration between nursing professionals and mathematicians.
  • To explore the potential of these tools to drive nursing development and improve clinical practice.

Main Methods:

  • Literature review on the application of mathematical models in nursing research.
  • Discussion of the impact of AI and Big Data on the integration of quantitative methods.
  • Analysis of the benefits derived from the use of mathematical modeling in nursing.

Main Results:

  • The utilization of mathematical models in nursing research has significantly increased in the last decade.
  • AI and Big Data are key drivers accelerating the adoption of advanced quantitative methods.
  • The integration of these tools offers substantial benefits for the advancement of nursing science.

Conclusions:

  • A strong synergy between nurses and mathematicians is crucial for advancing nursing research.
  • Enhanced nursing research through mathematical modeling can directly improve daily nursing practice and patient outcomes.
  • The continued integration of mathematical tools promises significant progress in the field of nursing.