AIMC Topic: Bias

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Evaluating and mitigating bias in AI-based medical text generation.

Nature computational science
Artificial intelligence (AI) systems, particularly those based on deep learning models, have increasingly achieved expert-level performance in medical applications. However, there is growing concern that such AI systems may reflect and amplify human ...

Detecting implicit biases of large language models with Bayesian hypothesis testing.

Scientific reports
Despite the remarkable performance of large language models (LLMs), such as generative pre-trained Transformers (GPTs), across various tasks, they often perpetuate social biases and stereotypes embedded in their training data. In this paper, we intro...

Chatbots for conducting systematic reviews in pediatric dentistry.

Journal of dentistry
OBJECTIVES: The performance of chatbots for discrete steps of a systematic review (SR) on artificial intelligence (AI) in pediatric dentistry was evaluated.

Demographic bias of expert-level vision-language foundation models in medical imaging.

Science advances
Advances in artificial intelligence (AI) have achieved expert-level performance in medical imaging applications. Notably, self-supervised vision-language foundation models can detect a broad spectrum of pathologies without relying on explicit trainin...

Artificial Intelligence Algorithms, Bias, and Innovation: Implications for Social Work.

Journal of evidence-based social work (2019)
PURPOSE: Artificial Intelligence (AI) technologies are rapidly expanding across diverse contexts. As the reach of AI continues to grow, there is a need to examine student perspectives on the increasing prevalence of AI and AI-based practice approache...

Biases in machine-learning models of human single-cell data.

Nature cell biology
Recent machine-learning (ML)-based advances in single-cell data science have enabled the stratification of human tissue donors at single-cell resolution, promising to provide valuable diagnostic and prognostic insights. However, such insights are sus...

Automation bias in AI-assisted detection of cerebral aneurysms on time-of-flight MR angiography.

La Radiologia medica
PURPOSE: To determine how automation bias (inclination of humans to overly trust-automated decision-making systems) can affect radiologists when interpreting AI-detected cerebral aneurysm findings in time-of-flight magnetic resonance angiography (TOF...

Bias Amplification to Facilitate the Systematic Evaluation of Bias Mitigation Methods.

IEEE journal of biomedical and health informatics
The future of artificial intelligence (AI) safety is expected to include bias mitigation methods from development to application. The complexity and integration of these methods could grow in conjunction with advances in AI and human-AI interactions....

UnBias: Unveiling Bias Implications in Deep Learning Models for Healthcare Applications.

IEEE journal of biomedical and health informatics
The rapid integration of deep learning-powered artificial intelligence systems in diverse applications such as healthcare, credit assessment, employment, and criminal justice has raised concerns about their fairness, particularly in how they handle v...

Is more data always better? On alternative policies to mitigate bias in Artificial Intelligence health systems.

Bioethics
The development and implementation of Artificial Intelligence (AI) health systems represent a great power that comes with great responsibility. Their capacity to improve and transform healthcare involves inevitable risks. A major risk in this regard ...