Radiomics-based machine learning models improve acute pancreatitis severity prediction

Ahmet Yasin Karkas et al.

AI - 20252025

Cite this work

Ahmet Yasin Karkas et al. (2025). Radiomics-based machine learning models improve acute pancreatitis severity prediction. AI - 2025

BibTeX

Publication details

Year: 2025
Type: Journal article

Research areas

Pancreatic diseases

Related publications

All publications

2026

IPMN risk assessment with subregional radiomics and deep learning

Andrea Mia Bejar, Eminenur Sen Tasci, Max Nelson, Halil Ertugrul Aktas, Katie Wu, Ziliang Hong, Elif Keles, Muhammed Enes Tasci, Frank H Miller, Michael B Wallace, Rajesh N Keswani, Gorkem Durak, Ulas Bagci

MAYO CLINIC INNOVATIONS IN GASTROENTEROLOGY AND HEPATOLOGY 2026: ARTIFICIAL INTELLIGENCE AND BEYOND

2026

Multimodal AI for early prediction of adverse clinical outcomes in acute pancreatitis

Ahmet Yasin Karkas, Yavuz B Taktak, Burak Gultekin, Ziliang Hong, Halil Ertugrul Aktas, Deniz Seyithanoglu, Timurhan Cebeci, Alper Akin, Ece Elustu, Kerem Arisin, Ali Canturk, Mehmet Ilhan, Naci Senkal, Michael B Wallace, Abraham F Bezuidenhout, Frank H Miller, Alpay Medetalibeyoglu, Mehmet Semih Cakir, Gorkem Durak, Ulas Bagci, Sukru Mehmet Erturk

Abdominal Radiology

2026

Multi-center radiomics-deep lEarning fusion model for stratifying IPMN malignancy risk on MRI

Bejar, A., et al

ISMRM 2026

2026

Upstream probabilistic meta-imputation for multimodal pediatric pancreatitis classification

Max A. Nelson, Elif Keles, Eminenur Sen Tasci, Merve Yazol, Halil Ertugrul Aktas, Ziliang Hong, Andrea Mia Bejar, Gorkem Durak, Oznur Leman Boyunaga, Ulas Bagci

IEEE ISBI 2026

2026

In-depth radiological and explainability analysis of deep learning predictions for IPMN risk stratification on MRI

Aktas, E. et al

ISMRM 2026