Copertina

Evaluating the Impact of Medical Image Reconstruction on Downstream AI Fairness and Performance

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wohlrapp, Matteo, Bubeck, Niklas, Rueckert, Daniel, Lotter, William
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

No Image, No Problem: End-to-End Multi-Task Cardiac Analysis from Undersampled k-Space
di: Zhang, Yundi, et al.
Pubblicazione: (2026)

On the Interplay of Human-AI Alignment,Fairness, and Performance Trade-offs in Medical Imaging
di: Luo, Haozhe, et al.
Pubblicazione: (2025)

Reconstruct or Generate: Exploring the Spectrum of Generative Modeling for Cardiac MRI
di: Bubeck, Niklas, et al.
Pubblicazione: (2025)

Simulating Clinical AI Assistance using Multimodal LLMs: A Case Study in Diabetic Retinopathy
di: Barakat, Nadim, et al.
Pubblicazione: (2025)

Comparing Computational Pathology Foundation Models using Representational Similarity Analysis
di: Mishra, Vaibhav, et al.
Pubblicazione: (2025)

DuetFair: Coupling Inter- and Intra-Subgroup Robustness for Fair Medical Image Segmentation
di: Tian, Yiqi, et al.
Pubblicazione: (2026)

Scientific Image Synthesis: Benchmarking, Methodologies, and Downstream Utility
di: Lin, Honglin, et al.
Pubblicazione: (2026)

Stable Diffusion Dataset Generation for Downstream Classification Tasks
di: Lomurno, Eugenio, et al.
Pubblicazione: (2024)

From Redaction to Restoration: Deep Learning for Medical Image Anonymization and Reconstruction
di: Kline, Adrienne, et al.
Pubblicazione: (2026)

Enhancing the Fairness and Performance of Edge Cameras with Explainable AI
di: Nguyen, Truong Thanh Hung, et al.
Pubblicazione: (2024)

Intersectional Fairness in Vision-Language Models for Medical Image Disease Classification
di: Zhang, Yupeng, et al.
Pubblicazione: (2025)

Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder
di: Marcus, Adam, et al.
Pubblicazione: (2026)

Downstream Transfer Attack: Adversarial Attacks on Downstream Models with Pre-trained Vision Transformers
di: Zheng, Weijie, et al.
Pubblicazione: (2024)

Targeted Downstream-Agnostic Attack
di: Lei, Zhuxin, et al.
Pubblicazione: (2026)

FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification
di: Gao, Yicheng, et al.
Pubblicazione: (2024)

Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis
di: Erdur, Ayhan Can, et al.
Pubblicazione: (2026)

Fake It Till You Make It: Using Synthetic Data and Domain Knowledge for Improved Text-Based Learning for LGE Detection
di: Jacob, Athira J, et al.
Pubblicazione: (2025)

Masked Contrastive Reconstruction for Cross-modal Medical Image-Report Retrieval
di: Wei, Zeqiang, et al.
Pubblicazione: (2023)

CompDiff: Hierarchical Compositional Diffusion for Fair and Zero-Shot Intersectional Medical Image Generation
di: Ibrahim, Mahmoud, et al.
Pubblicazione: (2026)

AdvDINO: Domain-Adversarial Self-Supervised Representation Learning for Spatial Proteomics
di: Su, Stella, et al.
Pubblicazione: (2025)

Tackling Hallucination from Conditional Models for Medical Image Reconstruction with DynamicDPS
di: Kim, Seunghoi, et al.
Pubblicazione: (2025)

Fairness Under Cover: Evaluating the Impact of Occlusions on Demographic Bias in Facial Recognition
di: Mamede, Rafael M., et al.
Pubblicazione: (2024)

Beyond Diagnosis: Evaluating Multimodal LLMs for Pathology Localization in Chest Radiographs
di: Gosai, Advait, et al.
Pubblicazione: (2025)

HOPPR Medical-Grade Platform for Medical Imaging AI
di: Slavkova, Kalina P., et al.
Pubblicazione: (2024)

Improving Performance, Robustness, and Fairness of Radiographic AI Models with Finely-Controllable Synthetic Data
di: Moroianu, Stefania L., et al.
Pubblicazione: (2025)

HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing
di: Chen, Ruyi, et al.
Pubblicazione: (2026)

Transfer or Self-Supervised? Bridging the Performance Gap in Medical Imaging
di: Zhao, Zehui, et al.
Pubblicazione: (2024)

Evaluating Strategies for Synthesizing Clinical Notes for Medical Multimodal AI
di: Marini, Niccolo, et al.
Pubblicazione: (2025)

Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives
di: Queiroz, Dilermando, et al.
Pubblicazione: (2025)

MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning
di: Pan, Jiazhen, et al.
Pubblicazione: (2025)

Fairness Evolution in Continual Learning for Medical Imaging
di: Ceccon, Marina, et al.
Pubblicazione: (2024)

HalluGen: Synthesizing Realistic and Controllable Hallucinations for Evaluating Image Restoration
di: Kim, Seunghoi, et al.
Pubblicazione: (2025)

What Sketch Explainability Really Means for Downstream Tasks
di: Bandyopadhyay, Hmrishav, et al.
Pubblicazione: (2024)

FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation
di: Teo, Christopher T. H, et al.
Pubblicazione: (2024)

INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models
di: Jin, Di, et al.
Pubblicazione: (2024)

FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification
di: Tian, Yu, et al.
Pubblicazione: (2024)

Evaluating Visual Explanations of Attention Maps for Transformer-based Medical Imaging
di: Chung, Minjae, et al.
Pubblicazione: (2025)

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
di: Bassi, Pedro R. A. S., et al.
Pubblicazione: (2024)

Learning to Evaluate the Artness of AI-generated Images
di: Chen, Junyu, et al.
Pubblicazione: (2023)

Leveraging Foundation Models for Histological Grading in Cutaneous Squamous Cell Carcinoma using PathFMTools
di: Diab, Abdul Rahman, et al.
Pubblicazione: (2025)