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Related Concept Videos

Impact01:30

Impact

133
Impact occurs when two bodies collide, leading to the application of impulsive forces between them. Analyzing impact mechanics involves considering two colliding particles moving along a line known as the line of impact, which passes through their centers and is perpendicular to the contact plane.
When particles with different initial velocities collide, they induce deformation by applying equal and opposite impulses. At the point of maximum deformation, the particles move together with...
133
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

111
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.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
111
Types of Impact01:30

Types of Impact

480
Impacts can be classified in various forms, primarily under two subgroups: central impact and oblique impact. A central impact occurs when two objects collide head-on, possessing opposite velocities aligned along the line of impact. Conversely, an oblique impact occurs when two objects collide at an angle, resulting in a modification of both direction and velocity.
The coefficient of restitution is a metric for understanding the dynamics of impacts. It quantifies the ratio of relative velocity...
480
Impact Loading01:19

Impact Loading

179
Impact loading occurs when a moving object collides with a stationary structure, such as a rod with a uniform cross-sectional area fixed at one end. Under these conditions, the rod absorbs the kinetic energy from the striking object, leading to deformation and subsequent stress development. As the rod returns to its original position and reaches maximum stress, the absorbed energy, initially manifested as kinetic energy, transforms entirely into strain energy.
In cases of elastic deformation,...
179
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

79
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
79
Relative Risk01:12

Relative Risk

107
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
107

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Direction of impact for explainable risk assessment modeling.

Emanuele Borgonovo1, Manel Baucells2, Antonio De Rosa1

  • 1Bocconi University, Milan, Italy.

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|February 25, 2025
PubMed
Summary

This study evaluates graphical indicators for model interpretability, finding that only PD functions consistently align with model properties. Analysts should also consider extrapolation risk when choosing visualization tools.

Keywords:
artificial intelligenceconvexitygraphical visualizationmachine learningmonotonicityrisk analysissensitivity analysis

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Area of Science:

  • Quantitative modeling
  • Risk analysis
  • Data visualization

Background:

  • Graphical indicators aid in visualizing input effects in complex models for decision-makers and risk analysts.
  • Limited understanding exists regarding the adequacy and consistency of various marginal effect indicators.

Purpose of the Study:

  • To investigate popular marginal effect indicators for consistency with quantitative model properties.
  • To examine indicator consistency concerning monotonicity, Lipschitz, and concavity properties.

Main Methods:

  • Evaluation of popular marginal effect indicators.
  • Assessment of consistency with model properties like monotonicity, Lipschitz, and concavity.
  • Consideration of model extrapolation risk.

Main Results:

  • Surprisingly, only Probability of Default (PD) functions demonstrated consistency with all examined model properties.
  • Individual Conditional Expectations (ICE) plots are recommended when extrapolation risk is manageable.

Conclusions:

  • PD functions offer reliable insights into model behavior, satisfying key consistency criteria.
  • The choice of visualization indicators must balance model consistency with the risk of extrapolation.