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Addressing fairness issues in deep learning|based medical image ...


Addressing fairness issues in deep learning-based medical image ...

In this survey, we thoroughly examine the current advancements in addressing fairness issues in MedIA, focusing on methodological approaches.

Addressing Fairness Issues in Deep Learning-Based Medical Image ...

Title:Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Review ... Abstract:Deep learning algorithms have ...

Addressing Fairness Issues in Deep Learning-Based Medical Image ...

In short, most of the large-scale foundation models and language models suffer from different levels of unfairness, due to domain gap, annotation noise, ...

[PDF] Addressing fairness issues in deep learning-based medical ...

Addressing fairness issues in deep learning-based medical image analysis: a systematic review · Zikang Xu, Yongshuo Zong, +2 authors S. K. Zhou · Published in npj ...

Addressing Fairness Issues in Deep Learning-Based ... - NASA ADS

Abstract. Deep learning algorithms have demonstrated remarkable efficacy in various medical image analysis (MedIA) applications.

(PDF) Addressing fairness issues in deep learning-based medical ...

Deep learning algorithms have demonstrated remarkable efficacy in various medical image analysis (MedIA) applications.

Addressing fairness in artificial intelligence for medical imaging

A plethora of work has shown that AI systems can systematically and unfairly be biased against certain populations in multiple scenarios.

Addressing fairness issues in deep learning-based medical image ...

AbstractDeep learning algorithms have demonstrated remarkable efficacy in various medical image analysis (MedIA) applications.

MediFormatica on LinkedIn: Addressing fairness issues in deep ...

Addressing fairness issues in deep learning-based medical image analysis: a systematic review - npj Digital Medicine Title: Addressing ...

(PDF) Addressing fairness in artificial intelligence for medical imaging

The field of medical imaging, where AI systems are beginning to be increasingly adopted, is no exception. Here we discuss the meaning of fairness in this area ...

Addressing Fairness Issues in Deep Learning-Based Medical Image ...

Deep learning algorithms have demonstrated remarkable efficacy in various medical image analysis (MedIA) applications. However, recent research highlights a ...

A survey of recent methods for addressing AI fairness and bias in ...

One approach to reducing bias in machine learning models is to balance the dataset, as training models with balanced and high-quality datasets may result in ...

Drop the shortcuts: image augmentation improves fairness and ...

It has been shown that AI models can learn race on medical images, leading to algorithmic bias. Our aim in this study was to enhance the fairness of medical ...

Medical AI fairness resources

Xu et al (2024), Addressing Fairness Issues in Deep Learning-based Medical Image Analysis: A Systematic Review, npj Digital Medicine. Seminal works on AI ...

Evaluating the Fairness of Deep Learning Uncertainty Estimates in ...

... address the issue of fairness, potential sources of biases, and the remaining challenges, for machine learning models in medical imaging. © 2023 CC-BY 4.0 ...

Toward fairness in artificial intelligence for medical image analysis

These tools are intended to help improve traditional human decision-making in medical imaging. However, biases introduced in the steps toward ...

Evaluating the Fairness of Deep Learning Uncertainty Estimates in...

In this work, we present the first exploration of the effect of popular fairness models on overcoming biases across subgroups in medical image ...

Bias in artificial intelligence for medical imaging

... machine learning, medical imaging, bias, fairness, radiology. Main ... Machine learning and bias in medical imaging: opportunities and challenges.

Addressing Fairness, Bias, and Appropriate Use of Artificial ...

A well-known example of machine learning bias, publicized by Joy Boulamwini in 2017 (Buolamwini, 2017), was the performance of facial detection algorithms when ...

Evaluating the Fairness of Deep Learning Uncertainty Estimates in ...

10 Citations ; Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Review · Zikang XuYongshuo ZongJun LiQingsong YaoS. K. Zhou.