5 papers
Automated Machine Learning in Radiomics: A Comparative Evaluation of Performance, Efficiency and Accessibility
Jose Lozano-Montoya, Emilio Soria-Olivas, Almudena Fuster-Matanzo +2
Automated machine learning (AutoML) frameworks can lower technical barriers for predictive and prognostic model development in radiomics by enabling researchers without programming…
A Pre-trained Foundation Model Framework for Multiplanar MRI Classification of Extramural Vascular Invasion and Mesorectal Fascia Invasion in Rectal Cancer
Yumeng Zhang, Shruti Atul Mali, Danial Khan +10
Objectives Accurate MRI-based identification of extramural vascular invasion (EVI) and mesorectal fascia invasion (MFI) is crucial for risk-stratified rectal cancer treatment. Howe…
Consensus in the Parliament of AI: Harmonized Multi-Region CT-Radiomics and Foundation-Model Signatures for Multicentre NSCLC Risk Stratification
Shruti Atul Mali, Zohaib Salahuddin, Danial Khan +13
Purpose: This study evaluates the impact of harmonization and multi-region feature integration on survival prediction in non-small cell lung cancer (NSCLC) patients. We assess the…
Agent-Based Output Drift Detection for Breast Cancer Response Prediction in a Multisite Clinical Decision Support System
Xavier Rafael-Palou, Jose Munuera, Ana Jimenez-Pastor +3
Modern clinical decision support systems can concurrently serve multiple, independent medical imaging institutions, but their predictive performance may degrade across sites due to…
Explainable Anatomy-Guided AI for Prostate MRI: Foundation Models and In Silico Clinical Trials for Virtual Biopsy-based Risk Assessment
Danial Khan, Zohaib Salahuddin, Yumeng Zhang +11
We present a fully automated, anatomically guided deep learning pipeline for prostate cancer (PCa) risk stratification using routine MRI. The pipeline integrates three key componen…