Fusion of clinical magnet resonance images and electronic health records promotes multimodal predictions of postoperative delirium

Abstract Brain morphometry derived from clinical imaging has an underexplored potential for the multimodal prediction of postoperative delirium (POD), an acute encephalopathy that can lead to long-term adverse outcomes or death. This study conducted a comprehensive analysis of patient trajectories,...

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主要な著者:	Niklas Giesa, Andrea Dell’Orco, Michael Scheel, Carsten Finke, Felix Balzer, Claudia Doris Spies, Maria Sekutowicz
フォーマット:	Artigo
言語:	Inglês
出版事項:	Nature Portfolio 2025-12-01
シリーズ:	Scientific Reports
主題:	Machine learning Postoperative delirium Feature fusion strategies Electronic health records Brain morphometry
オンライン･アクセス:	https://doi.org/10.1038/s41598-025-31693-9
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