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Related Concept Videos

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Self-Help Support Groups

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Self-help support groups are voluntary, community-based organizations that provide a platform for individuals with shared concerns to exchange support, insights, and practical strategies for coping with life challenges. Typically led by group members or paraprofessionals, these groups form a cornerstone of mental health care, especially in reaching populations that are underserved by traditional healthcare systems.
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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.
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A coplanar force system refers to a set of forces that all lie in the same plane and are subject to different reactions between the point of contact and the supports. Understanding how different types of supports affect coplanar forces is crucial for designing safe and reliable structures that can withstand external loads.
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In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
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Support reactions in three dimensions help maintain the stability and equilibrium of various structures and systems. These reactions prevent the system from translating and rotating, ensuring the design can withstand external forces and perform its intended function efficiently and safely. Some of the supports providing support reactions in three dimensions are discussed below:
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Decision Support Systems in Oncology.

Seán Walsh1, Evelyn E C de Jong1, Janna E van Timmeren1

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Precision medicine in oncology faces challenges due to human cognitive limits. Multifactorial decision support systems (DSSs) offer a solution by integrating data for optimized patient care.

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Area of Science:

  • Oncology
  • Health Informatics
  • Artificial Intelligence in Medicine

Background:

  • Precision medicine aims to tailor healthcare, with oncology leading adoption.
  • Human cognitive limitations hinder managing complex biomarker and treatment data.
  • Current decision-making methods are insufficient for precision medicine's complexity.

Purpose of the Study:

  • To explore multifactorial decision support systems (DSSs) as a solution for precision medicine.
  • To highlight the role of artificial intelligence in oncology decision-making.
  • To provide an overview of DSSs' challenges, opportunities, and impact on clinical decisions.

Main Methods:

  • Overview of decision support systems (DSSs) leveraging artificial intelligence.
  • Integration of diverse data (clinical, imaging, genetic, cost) for predictive models.
  • Comparison of personalized outcomes (toxicity, efficacy, cost) for care pathway decisions.

Main Results:

  • DSSs integrate complex data to create validated predictive models.
  • DSSs enable strategic and tactical decision support in oncology workflows.
  • Reimbursement policies increasingly mandate DSS use for specific treatments like proton therapy.

Conclusions:

  • Decision support systems are essential for realizing precision medicine in oncology.
  • AI-powered DSSs address cognitive limitations and data complexity in healthcare.
  • DSSs are crucial for optimizing efficacy, economy, and patient outcomes in cancer care.