21 citations · 47 across the 6 of their papers we have counts for
7 papers
Grounding Clinical AI Competency in Human Cognition Through the Clinical World Model and Skill-Mix Framework
Seyed Amir Ahmad Safavi-Naini, Elahe Meftah, Josh Mohess +11
The competency of any intelligent agent is bounded by its formal account of the world in which it operates. Clinical AI lacks such an account. Existing frameworks address evaluatio…
The added value for MRI radiomics and deep-learning for glioblastoma prognostication compared to clinical and molecular information
D. Abler, O. Pusterla, A. Joye-Kühnis +19
Background: Radiomics shows promise in characterizing glioblastoma, but its added value over clinical and molecular predictors has yet to be proven. This study assessed the added v…
ISLES'24 -- A Real-World Longitudinal Multimodal Stroke Dataset
Evamaria Olga Riedel, Ezequiel de la Rosa, The Anh Baran +18
Stroke remains a leading cause of global morbidity and mortality, imposing a heavy socioeconomic burden. Advances in endovascular reperfusion therapy and CT and MR imaging for trea…
ISLES'24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand?
Ezequiel de la Rosa, Ruisheng Su, Mauricio Reyes +37
Accurate estimation of brain infarction (i.e., irreversibly damaged tissue) is critical for guiding treatment decisions in acute ischemic stroke. Reliable infarct prediction inform…
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew +55
Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable A…
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
Florian Kofler, Felix Meissen, Felix Steinbauer +103
A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…