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Related Concept Videos

Bias01:22

Bias

7.6K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
7.6K
Ethics and Bioethics01:22

Ethics and Bioethics

3.2K
Ethics is a philosophical study of moral actions. Ethics attempts to determine what is valuable for individuals and society. It examines the rational justification of moral judgments and analyzes what is morally just, fair, and right. Bioethics is a sub-discipline of applied ethics that analyzes the philosophical, social, and legal issues in life sciences and medicine. Ethical theories serve as a foundation for decision-making and represent the viewpoints from which people seek direction. They...
3.2K
Ethical Issues01:27

Ethical Issues

2.3K
Nurses are essential in patient care, upholding the ethical principles of their profession and effectively navigating ethical dilemmas. Neglecting ethical issues can lead to inadequate patient care, compromised therapeutic relationships, and moral distress among healthcare workers.
Ethical Concerns in Healthcare:
2.3K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

1.4K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
1.4K
Motivational Bias01:25

Motivational Bias

432
Cognitive bias results from limitations in thinking and information processing, leading to systematic errors in judgment. Conversely, motivational bias stems from personal desires or emotions, causing distortions in perception to align with self-interest. Motivational bias influences how individuals perceive and attribute causes to events, often shaped by personal needs, goals, and self-esteem preservation. This bias can distort judgment, leading to inaccurate assessments of success, failure,...
432
Halo Effect01:27

Halo Effect

563
The halo effect is a cognitive bias in which an individual's overall impression influences judgments about their specific traits. This psychological phenomenon leads people to associate positive characteristics with those they perceive as generally good and negative characteristics with those they view as bad. This effect is particularly influential in social perception, professional evaluations, and decision-making processes.The Psychological Basis of the Halo EffectThe halo effect is rooted...
563

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Related Experiment Video

Updated: May 6, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

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Session Introduction: Fairness and Bias in Biomedical AI/ML: Defining Goals and Putting Them Into Practice.

Nicole Martinez-Martin1, Abdoul Jalil Djiberou Mahamadou2, Madelena Ng3

  • 1Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, California 94025, USA, nicolemz@stanford.edu.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|February 27, 2026
PubMed
Summary

Ensuring artificial intelligence and machine learning (AI/ML) models are fair and unbiased across diverse populations remains a challenge in biomedical applications. Addressing differing researcher perspectives on bias and fairness is crucial for ethical AI/ML development.

Area of Science:

  • Biomedical informatics
  • Artificial intelligence

Related Experiment Videos

Last Updated: May 6, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.9K
  • Machine learning
  • Computational biology
  • Background:

    • Generalizability and accuracy of artificial intelligence and machine learning (AI/ML) across diverse populations are critical for ethical biomedical applications.
    • Bias and fairness in AI/ML are recognized challenges, yet conceptual and operational differences among researchers hinder progress.
    • Disparities in AI/ML performance across demographic groups raise significant ethical concerns in healthcare.