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Related Concept Videos

Theoretical Approaches to Psychological Disorder01:29

Theoretical Approaches to Psychological Disorder

The development of psychological disorders, which are characterized by deviant, maladaptive, and personally distressing behaviors, has been explored through several theoretical approaches.
Biological approach
The biological approach posits that internal, organic factors are the primary causes of such disorders. This perspective emphasizes brain structure and function, genetic predispositions, and neurotransmitter imbalances. For example, schizophrenia has been associated with both genetic...
Dimensions of Health and Illness01:21

Dimensions of Health and Illness

The factors influencing the health-illness continuum can be internal or external and may or may not be under conscious control. They are related to the following eight human dimensions, and each dimension is interrelated to one other.
Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

Depressive disorders result from a complex interplay of biological, psychological, and sociocultural factors, each contributing uniquely to the development and persistence of the condition. Understanding these factors provides critical insight into the multifaceted nature of depression.
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
Factors Affecting Illness01:18

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness, disability,...
Combined Effects of Drugs: Synergism01:27

Combined Effects of Drugs: Synergism

Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...

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Updated: May 8, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
05:10

Multidisciplinary Approach to Obesity Management: A Case Report

Published on: May 30, 2025

Comorbidity: a multidimensional approach.

Enrico Capobianco1, Pietro Lio'

  • 1Center for Computational Science (CCS), Miller School of Medicine, University of Miami, Miami, FL 33136, USA; Laboratory of Integrative Systems Medicine (LISM), Institute of Clinical Physiology (IFC), National Research Council (CNR), Pisa 56124, Italy.

Trends in Molecular Medicine
|August 17, 2013
PubMed
Summary
This summary is machine-generated.

Computational approaches can redefine the study of comorbidity by viewing patient conditions as a system. This network analysis offers a dynamic way to understand disease links and patient risk.

Keywords:
clusteringcomorbiditydynamic mappinginferencemultidimensionalitypatient disease network

Related Experiment Videos

Last Updated: May 8, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
05:10

Multidisciplinary Approach to Obesity Management: A Case Report

Published on: May 30, 2025

Area of Science:

  • Computational medicine
  • Systems biology
  • Network science

Background:

  • Comorbidity, the presence of multiple diseases in one patient, presents significant research complexity.
  • Existing meta-analysis studies often integrate evidence but may not fully capture the dynamic interplay of conditions.
  • The uncertainty in deciphering comorbidity increases with the number of associated morbidities.

Purpose of the Study:

  • To propose a reformulation of comorbidity research through computational methods.
  • To emphasize a systems approach for a generalized model of multimorbidity.
  • To highlight dynamic network inference for analyzing disease links and risk.

Main Methods:

  • Adopting a systems approach to model comorbidity as an ensemble.
  • Utilizing dynamic network inference to analyze relationships between morbidities.
  • Integrating multiple dimensions of comorbidity complexity for translational research.

Main Results:

  • A systems approach provides a generalizable model for multimorbidity.
  • Dynamic network inference enables the analysis of links among morbidities and risk evaluation.
  • Simultaneous consideration of multiple dimensions is key for translating computational findings into medical practice.

Conclusions:

  • Computational methods, specifically systems and network approaches, offer a new paradigm for understanding comorbidity.
  • These approaches can potentially shift medical practice by providing a dynamic and integrated view of patient conditions.
  • The translation of computational insights into clinical practice hinges on considering the multifaceted nature of comorbidity.