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Bias

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Ascertaining provider-level implicit bias in electronic health records with rules-based natural language processing: A pilot study in the case of prostate cancer.

PloS one
PURPOSE: Implicit, unconscious biases in medicine are personal attitudes about race, ethnicity, gender, and other characteristics that may lead to discriminatory patterns of care. However, there is no consensus on whether implicit bias represents a t...

Attention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.

Scientific reports
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for class...

Bias in machine learning applications to address non-communicable diseases at a population-level: a scoping review.

BMC public health
BACKGROUND: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population healt...

Enhancing consistency and mitigating bias: A data replay approach for incremental learning.

Neural networks : the official journal of the International Neural Network Society
Deep learning systems are prone to catastrophic forgetting when learning from a sequence of tasks, as old data from previous tasks is unavailable when learning a new task. To address this, some methods propose replaying data from previous tasks durin...

On spectral bias reduction of multi-scale neural networks for regression problems.

Neural networks : the official journal of the International Neural Network Society
In this paper, we derive diffusion equation models in the spectral domain to study the evolution of the training error of two-layer multiscale deep neural networks (MscaleDNN) (Cai and Xu, 2019; Liu et al., 2020), which is designed to reduce the spec...

Ethical and security challenges in AI for forensic genetics: From bias to adversarial attacks.

Forensic science international. Genetics
Forensic scientists play a crucial role in assigning probabilities to evidence based on competing hypotheses, which is fundamental in legal contexts where propositions are presented usually by prosecution and defense. The likelihood ratio (LR) is a w...

Reducing bias in source-free unsupervised domain adaptation for regression.

Neural networks : the official journal of the International Neural Network Society
Due to data privacy and storage concerns, Source-Free Unsupervised Domain Adaptation (SFUDA) focuses on improving an unlabelled target domain by leveraging a pre-trained source model without access to source data. While existing studies attempt to tr...

Humor as a window into generative AI bias.

Scientific reports
A preregistered audit of 600 images by generative AI across 150 different prompts explores the link between humor and discrimination in consumer-facing AI solutions. When ChatGPT updates images to make them "funnier", the prevalence of stereotyped gr...

Bias Mitigation in Primary Health Care Artificial Intelligence Models: Scoping Review.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) predictive models in primary health care have the potential to enhance population health by rapidly and accurately identifying individuals who should receive care and health services. However, these models als...

Bias in adjudication: Investigating the impact of artificial intelligence, media, financial and legal institutions in pursuit of social justice.

PloS one
The latest global progress report highlights numerous challenges in achieving justice goals, with bias in artificial intelligence (AI) emerging as a significant yet underexplored issue. This paper investigates the role of AI in addressing bias within...