Ethics and Fairness in Medical Imaging, Kartoniert / Broschiert
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, O
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Esther Puyol-Antón, John S. H. Baxter, Islem Rekik, Roy Eagleson, Ghada Zamzmi, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Eike Petersen
- Verlag:
- Springer, 10/2024
- Einband:
- Kartoniert / Broschiert, Paperback
- Sprache:
- Englisch
- ISBN-13:
- 9783031727863
- Artikelnummer:
- 12017764
- Umfang:
- 208 Seiten
- Gewicht:
- 324 g
- Maße:
- 235 x 155 mm
- Stärke:
- 12 mm
- Erscheinungstermin:
- 13.10.2024
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
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 Alzheimer's 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.