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Related Concept Videos

Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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Decision Making: P-value Method01:09

Decision Making: P-value Method

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Reason and Intuition01:37

Reason and Intuition

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Heuristics01:21

Heuristics

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Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
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Data Validation01:03

Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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Related Experiment Video

Updated: Mar 31, 2026

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
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Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

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Lessons of War: Turning Data Into Decisions.

Jonathan A Forsberg1, Benjamin K Potter2, Matthew B Wagner1

  • 1Department of Surgery at the Uniformed Services University of the Health Sciences and the Walter Reed National Military Medical Center, Bethesda, MD USA ; Regenerative Medicine Department, Naval Medical Research Center, Silver Spring, MD USA ; Surgical Critical Care Initiative (SC2i), Bethesda, MD, USA.

Ebiomedicine
|October 27, 2015
PubMed
Summary

Predicting combat wound healing is possible using clinical and biomarker data. Advanced analytics created a model that may improve patient outcomes and reduce costs in both military and civilian settings.

Keywords:
Clinical decision supportCombat traumaDecision analysisInflammationWound healing

Related Experiment Videos

Last Updated: Mar 31, 2026

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

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Area of Science:

  • Biomedical Engineering
  • Computational Biology
  • Trauma Surgery

Background:

  • Recent conflicts generated numerous critically wounded service members.
  • A study collected biomarker and clinical data from 73 patients with 116 life-threatening combat wounds.
  • The goal was to predict the likelihood of wound failure.

Purpose of the Study:

  • To develop a predictive model for combat wound healing.
  • To assess the role of systemic inflammatory conditions in local wound failure.
  • To determine generalizability to civilian trauma patients.

Main Methods:

  • Collected clinical data, serum, wound effluent, and tissue from patients.
  • Quantified inflammatory cytokines and gene expression targets.
  • Utilized computer-intensive methods for prognostic model derivation and validation.
  • Evaluated a cohort of civilian trauma patients for similar inflammatory responses.

Main Results:

  • The best models combined clinical observation with biomarker data (serum and wound effluent).
  • A Random Forest model with ten variables achieved high accuracy (AUC 0.79).
  • Civilian trauma patients showed similar inflammatory responses and wound failure rates.

Conclusions:

  • Advanced analytics created a potentially generalizable decision support tool for wound healing.
  • The model may improve clinical decision-making and reduce healthcare costs.
  • Analysis of inflammatory data in critically ill patients can inform treatment strategies.