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E-raamat: Ethics and Fairness in Medical Imaging: Second International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and Third International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, Octobe

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Ethics and Fairness in Medical Imaging: Second International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and Third International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, OctobeSuurem pilt
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This book constitutes the refereed proceedings of the Second International Workshop, FAIMI 2024, and the Third International Workshop, EPIMI 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, in October 2024.

The 17 full papers presented in this book were carefully reviewed and selected from 21 submissions.
FAIMI aimed to raise awareness about potential fairness issues in machine learning within the context of biomedical image analysis.
The instance of EPIMI concentrates on topics surrounding open science, taking a critical lens on the subject.

FAIMI: Slicing Through Bias: Explaining Performance Gaps in Medical
Image Analysis using Slice Discovery Methods.- Dataset Distribution Impacts
Model Fairness: Single vs Multi-Task Learning.- AI Fairness in Medical
Imaging: Controlling for Disease Severity.- Fair and Private CT Contrast
Agent Detection.- Mitigating Overdiagnosis Bias in CNN-Based Alzheimers
Disease Diagnosis for the Elderly.- Fair AI Outcomes Without Sacrificing
Group Gains .- All you need is a guiding hand: mitigating shortcut bias in
deep learning models for medical imaging.- Exploring Fairness in
State-of-the-Art Pulmonary Nodule Detection Algorithms.- Quantifying the
Impact of Population Shift Across Age and Sex for Abdominal Organ
Segmentation.- BMFT: Achieving Fairness via Bias-based Weight Masking
Fine-tuning.- Using Backbone Foundation Model for Evaluating Fairness in
Chest Radiography Without Demographic Data.- Do sites benefit equally from
distributed learning in medical image analysis.- Cycle-GANs generated
difference maps to interpret race prediction from medical images.- On Biases
in a UK Biobank-based Retinal Image Classification Model.- Investigating
Gender Bias in Lymph-node Segmentation with Anatomical Priors.- EPIMI:
Assessing the Impact of Sociotechnical Harms in AI-based Medical Image
Analysis.- Practical and Ethical Considerations for Generative AI in Medical
Imaging.
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