Background: Attention Deficit/Hyperactivity Disorder (ADHD) is a highly prevalent neurodevelopmental disorder, but its diagnosis remains constrained. This study aimed to identify potential candidate ...
AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
The ML model stratifies HCC patients by mortality risk, guiding treatment decisions between liver transplantation and surgical resection. The model demonstrated improved survival outcomes, with a 54% ...
Abstract: Federated learning (FL) is a promising distributed machine learning framework for mobile networks, where an aggregation server produces a global model by aggregating the local models from ...
Introduction: Extended viewing of 3D content can induce fatigue symptoms. Thus, fatigue assessment is crucial for enhancing the user experience and optimizing the performance of stereoscopic 3D ...
ABSTRACT: Background: In Cameroon, little is known about the visual repercussions of neurological disorders, according to the available literature. Local data could improve screening, prevention, and ...
The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care. Today, over 30 ...
I-JEPA is a self-supervised learning method for generating semantic image representations without relying on hand-crafted data augmentations often used in invariance-based methods. It operates on the ...
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