Share on Pinterest An AI tool may be able to predict GVHD risk, prompting earlier treatment to prevent complications. Image credit: Victor Bordera/Stocksy An AI-based tool may be able to predict the ...

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The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

This paper presents a machine learning–based nowcasting framework for estimating quarterly non-oil GDP growth in the Gulf Cooperation Council (GCC) countries. Leveraging machine learning models ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

The delayed coker unit (DCU) at TotalEnergies’ Port Arthur refinery's is a complex system that thermally cracks heavy residual oils into lighter, more valuable oil products and petroleum coke. As ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...

In this tutorial, we explore LitServe, a lightweight and powerful serving framework that allows us to deploy machine learning models as APIs with minimal effort. We build and test multiple endpoints ...

In an era where artificial intelligence drives critical business decisions, Nikhil Dodda emphasizes that maintaining machine learning model performance is as crucial as building them. Model deployment ...