Fairness of AI in Medical Imaging

Third International Workshop, FAIMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings

AvEsther Puyol-Antón,Enzo Ferrante

Häftad, Engelska, 2025

Del 15976 i serien Lecture Notes in Computer Science

642 kr

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This book constitutes the refereed proceedings of the Third International Workshop, FAIMI 2025, held in conjunction with MICCAI 2025, Daejeon, South Korea, in September 23, 2025.The 21 full papers presented in this book were carefully reviewed and selected from 29 submissions.FAIMI aimed to raise awareness about potential fairness issues in machine learning within the context of biomedical image analysis.

Produktinformation

Utgivningsdatum:2025-09-19
Mått:155 x 235 x 13 mm
Vikt:359 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:220
Förlag:Springer Nature Switzerland AG
ISBN:9783032058690

Utforska kategorier

Innehållsförteckning

.- LTCXNet: Tackling Long-Tailed Multi-Label Classification and RacialBias in Chest X-Ray Analysis..- Fairness and Robustness of CLIP-Based Models for Chest X-rays..- ShortCXR: Benchmarking Self-Supervised Learning Methods forShortcut Mitigation in Chest X-Ray Interpretation..- How Fair Are Foundation Models? Exploring the Role of CovariateBias in Histopathology..- The Cervix in Context: Bias Assessment in Preterm Birth Prediction..- Identifying Gender-Specific Visual Bias Signals in Skin Lesion Classification..- Fairness-Aware Data Augmentation for Cardiac MRI usingText-Conditioned Diffusion Models..- Exploring the interplay of label bias with subgroup size and separability:A case study in mammographic density classification..- Does a Rising Tide Lift All Boats? Bias Mitigation for AI-based CMRSegmentation..- MIMM-X: Disentangeling Spurious Correlations for Medical ImageAnalysis..- Predicting Patient Self-reported Race From Skin Histological Imageswith Deep Learning..- Robustness and sex differences in skin cancer detection: logisticregression vs CNNs..- Sex-based Bias Inherent in the Dice Similarity Coefficient: A ModelIndependent Analysis for Multiple Anatomical Structures..- The Impact of Skin Tone Label Granularity on the Performance andFairness of AI Based Dermatology Image Classification Models..- Causal Representation Learning with Observational Grouping for CXRClassification..- Invisible Attributes, Visible Biases: Exploring Demographic Shortcutsin MRI-based Alzheimer’s Disease Classification..- Fair Dermatological Disease Diagnosis through Auto-weightedFederated Learning and Performance-aware Personalization..- Assessing Annotator and Clinician Biases in an Open-Source-BasedTool Used to Generate Head CT Segmentations for Deep LearningTraining..- meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis..- Revisiting the Evaluation Bias Introduced by Frame SamplingStrategies in Surgical Video Segmentation Using SAM2..- Disentanglement and Assessment of Shortcuts in OphthalmologicalRetinal Imaging Exams.

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Fairness of AI in Medical Imaging

Third International Workshop, FAIMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 23, 2025, Proceedings

AvEsther Puyol-Antón,Enzo Ferrante

Häftad, Engelska, 2025

Del 15976 i serien Lecture Notes in Computer Science

642 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

Beskrivning

Produktinformation

Utgivningsdatum:2025-09-19
Mått:155 x 235 x 13 mm
Vikt:359 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:220
Förlag:Springer Nature Switzerland AG
ISBN:9783032058690

Utforska kategorier

Innehållsförteckning

.- LTCXNet: Tackling Long-Tailed Multi-Label Classification and RacialBias in Chest X-Ray Analysis..- Fairness and Robustness of CLIP-Based Models for Chest X-rays..- ShortCXR: Benchmarking Self-Supervised Learning Methods forShortcut Mitigation in Chest X-Ray Interpretation..- How Fair Are Foundation Models? Exploring the Role of CovariateBias in Histopathology..- The Cervix in Context: Bias Assessment in Preterm Birth Prediction..- Identifying Gender-Specific Visual Bias Signals in Skin Lesion Classification..- Fairness-Aware Data Augmentation for Cardiac MRI usingText-Conditioned Diffusion Models..- Exploring the interplay of label bias with subgroup size and separability:A case study in mammographic density classification..- Does a Rising Tide Lift All Boats? Bias Mitigation for AI-based CMRSegmentation..- MIMM-X: Disentangeling Spurious Correlations for Medical ImageAnalysis..- Predicting Patient Self-reported Race From Skin Histological Imageswith Deep Learning..- Robustness and sex differences in skin cancer detection: logisticregression vs CNNs..- Sex-based Bias Inherent in the Dice Similarity Coefficient: A ModelIndependent Analysis for Multiple Anatomical Structures..- The Impact of Skin Tone Label Granularity on the Performance andFairness of AI Based Dermatology Image Classification Models..- Causal Representation Learning with Observational Grouping for CXRClassification..- Invisible Attributes, Visible Biases: Exploring Demographic Shortcutsin MRI-based Alzheimer’s Disease Classification..- Fair Dermatological Disease Diagnosis through Auto-weightedFederated Learning and Performance-aware Personalization..- Assessing Annotator and Clinician Biases in an Open-Source-BasedTool Used to Generate Head CT Segmentations for Deep LearningTraining..- meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis..- Revisiting the Evaluation Bias Introduced by Frame SamplingStrategies in Surgical Video Segmentation Using SAM2..- Disentanglement and Assessment of Shortcuts in OphthalmologicalRetinal Imaging Exams.

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