Prediction of crystal structures of organic molecules is a critical task in many industries, especially in pharmaceuticals ...
For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...
Most organizations rely on traditional last-touch attribution, a simple model that assigns 100% credit to the last engagement ...
Abstract: Graph machine learning has been extensively studied in both academia and industry. Although booming with a vast number of emerging methods and techniques, most of the literature is built on ...
Abstract: Graph contrastive learning is usually performed by first conducting Graph Data Augmentation (GDA) and then employing a contrastive learning pipeline to train GNNs. As we know that GDA is an ...
Apple has been using this laptop design for about four years now, since it released the M1 Pro and M1 Max versions of the ...
The conflict of interest statement was erroneously given as “YL was employed by Yizhun Medical AI Co. Ltd. The remaining authors declare that the research was conducted in the absence of any ...
Objectives To evaluate whether postpartum haemorrhage (PPH) can be predicted using both machine learning (ML) and traditional statistical models. Design Diagnostic systematic review and meta-analysis ...
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