Cover Image

Machine Learning based Analysis for Radiomics Features Robustness in Real-World Deployment Scenarios

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Khan, Sarmad Ahmad, Bernatz, Simon, Moslehi, Zahra, Buettner, Florian
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DATS: Distance-Aware Temperature Scaling for Calibrated Class-Incremental Learning
by: Serra, Giuseppe, et al.
Published: (2025)

Federated Continual Learning Goes Online: Uncertainty-Aware Memory Management for Vision Tasks and Beyond
by: Serra, Giuseppe, et al.
Published: (2024)

Improving Perturbation-based Explanations by Understanding the Role of Uncertainty Calibration
by: Decker, Thomas, et al.
Published: (2025)

Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations
by: Decker, Thomas, et al.
Published: (2025)

Better Uncertainty Calibration via Proper Scores for Classification and Beyond
by: Gruber, Sebastian G., et al.
Published: (2022)

A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
by: Gruber, Sebastian G., et al.
Published: (2023)

Mind the Gap: A Framework for Assessing Pitfalls in Multimodal Active Learning
by: Eisenhardt, Dustin, et al.
Published: (2026)

Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control
by: Müller, Arthur, et al.
Published: (2021)

How to Leverage Predictive Uncertainty Estimates for Reducing Catastrophic Forgetting in Online Continual Learning
by: Serra, Giuseppe, et al.
Published: (2024)

MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model
by: Koebler, Alexander, et al.
Published: (2025)

Beyond Overconfidence: Foundation Models Redefine Calibration in Deep Neural Networks
by: Hekler, Achim, et al.
Published: (2025)

Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance
by: Decker, Thomas, et al.
Published: (2024)

Frontiers of Deep Learning: From Novel Application to Real-World Deployment
by: Xie, Rui
Published: (2024)

Cross-Vendor Reproducibility of Radiomics-based Machine Learning Models for Computer-aided Diagnosis
by: Chaudhary, Jatin, et al.
Published: (2024)

No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
by: Szász, Attila, et al.
Published: (2025)

Holonic Learning: A Flexible Agent-based Distributed Machine Learning Framework
by: Esmaeili, Ahmad, et al.
Published: (2023)

Automated Machine Learning in Radiomics: A Comparative Evaluation of Performance, Efficiency and Accessibility
by: Lozano-Montoya, Jose, et al.
Published: (2026)

Provably Better Explanations with Optimized Aggregation of Feature Attributions
by: Decker, Thomas, et al.
Published: (2024)

From Entropy to Calibrated Uncertainty: Training Language Models to Reason About Uncertainty
by: Jenane, Azza, et al.
Published: (2026)

Learning to Play Piano in the Real World
by: Zeulner, Yves-Simon, et al.
Published: (2025)

Cost Function Estimation Using Inverse Reinforcement Learning with Minimal Observations
by: Mehrdad, Sarmad, et al.
Published: (2025)

The Pump Scheduling Problem: A Real-World Scenario for Reinforcement Learning
by: Donâncio, Henrique, et al.
Published: (2022)

Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment
by: Hwang, Uiwon, et al.
Published: (2026)

Deploying Privacy Guardrails for LLMs: A Comparative Analysis of Real-World Applications
by: Asthana, Shubhi, et al.
Published: (2025)

BrainMetDetect: Predicting Primary Tumor from Brain Metastasis MRI Data Using Radiomic Features and Machine Learning Algorithms
by: Sadeghsalehi, Hamidreza
Published: (2024)

DurableUn: Quantization-Induced Recovery Attacks in Machine Unlearning
by: Khan, Abdullah Ahmad, et al.
Published: (2026)

Deploying Geospatial Foundation Models in the Real World: Lessons from WorldCereal
by: Butsko, Christina, et al.
Published: (2025)

Disentangling Mean Embeddings for Better Diagnostics of Image Generators
by: Gruber, Sebastian G., et al.
Published: (2024)

Deploying Tiny LVLM Judges for Real-World Evaluation of Chart Models: Lessons Learned and Best Practices
by: Laskar, Md Tahmid Rahman, et al.
Published: (2025)

Personalized Federated Learning Techniques: Empirical Analysis
by: Khan, Azal Ahmad, et al.
Published: (2024)

Financial Management System for SMEs: Real-World Deployment of Accounts Receivable and Cash Flow Prediction
by: Małkus, Bartłomiej, et al.
Published: (2025)

Fairness and Robustness in Machine Unlearning
by: Tran, Khoa, et al.
Published: (2025)

Adversarially Robust Deepfake Detection via Adversarial Feature Similarity Learning
by: Khan, Sarwar
Published: (2024)

Scientific Inference With Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena
by: Freiesleben, Timo, et al.
Published: (2022)

Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
by: Toups, Connor, et al.
Published: (2023)

Toward Global Intent Inference for Human Motion by Inverse Reinforcement Learning
by: Mehrdad, Sarmad, et al.
Published: (2026)

Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention
by: Koebler, Alexander, et al.
Published: (2025)

Power Transformer Health Index and Life Span Assessment: A Comprehensive Review of Conventional and Machine Learning based Approaches
by: Zahra, Syeda Tahreem, et al.
Published: (2025)

NeoRL-2: Near Real-World Benchmarks for Offline Reinforcement Learning with Extended Realistic Scenarios
by: Gao, Songyi, et al.
Published: (2025)

Efficient Unsupervised Shortcut Learning Detection and Mitigation in Transformers
by: Kuhn, Lukas, et al.
Published: (2025)