Abstract: Heart disease remains one of the foremost causes of mortality worldwide, highlighting the need for timely diagnosis and tailored treatment strategies. Although conventional diagnostic ...

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 ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

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., ...

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 how to harness Apache Spark’s techniques using PySpark directly in Google Colab. We begin by setting up a local Spark session, then progressively move through ...

Tumor neoantigens possess high specificity and immunogenicity, making them crucial targets for personalized cancer immunotherapies such as mRNA vaccines and T-cell therapies. However, experimental ...