4 papers · 1 filter
Explainability in mulimodal deep transformation models for stroke outcome prediction
Lisa Herzog, Jonas Brändli, Maurice Schneeberger +7
Multimodal prediction models based on imaging and clinical data are increasingly used for clinical decision support, yet their interpretability remains limited. We present multimod…
Leptomeningeal Collateral Detection on DSA via Vessel-Graph Neural Networks
Junyong Cao, Hakim Baazaoui, Chinmay Prabhakar +5
Leptomeningeal collaterals (LMCs) are an important prognostic factor in acute ischemic stroke. Existing automated methods rely on CT angiography (CTA), but individual LMCs are ofte…
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…
Outcome prediction and individualized treatment effect estimation in patients with large vessel occlusion stroke
Lisa Herzog, Pascal Bühler, Ezequiel de la Rosa +2
Mechanical thrombectomy has become the standard of care in patients with stroke due to large vessel occlusion (LVO). However, only 50% of successfully treated patients show a favor…