Identifying optimal catalyst materials for specific reactions is crucial to advance energy storage technologies and sustainable chemical processes. To screen catalysts, scientists must understand ...
This study aimed to determine if an ensemble (stacking) model that integrates three independently developed base models can reliably predict patients’ neurological outcomes following out-of-hospital ...
Cardiovascular diseases account for approximately 80% of all deaths caused by known medical conditions, making them the leading cause of mortality worldwide. The present study investigates the use of ...
Youth mental health-related problems and disorders have garnered increased attention due to global prevalence estimates that have, in some cases, increased following the COVID-19 pandemic. Various ...
Abstract: Advancing Multimodal AI for Integrated Understanding and Generation explores the transformative potential of multimodal artificial intelligence (AI), which integrates diverse data types such ...
The PlantIF framework consists of image and text feature extractors, semantic space encoders, and a multimodal feature fusion module. Image and text feature extractors are used to present visual and ...
Cross-stage validation of a multimodal machine learning model to predict pathological complete response to neoadjuvant chemotherapy or chemoimmunotherapy in resectable stage III non–small cell lung ...
A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona (UBneuro) has applied advanced artificial intelligence techniques to better ...
INDIANAPOLIS — As a Purdue University master’s degree student in electrical and computer engineering in West Lafayette, Karen D’Souza was impressed by the depth and breadth of the research offered ...
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