The Lancet

Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA…

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
IEEE

MLXOps4Medic: A Service Framework for Machine Learning and Explainability Operations in Medical Imaging AI Development

Integrating AI models with the medical domain is challenging as it involves more complex workflows compared to traditional machine learning operations (MLOps). Requirements such as model performance ...
marktechpost

How to Build an End-to-End Data Engineering and Machine Learning Pipeline with Apache Spark and PySpark

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 ...
C&EN

Study on the Adsorption Performance of Ionic Liquids Based on Molecular Dynamics and Interpretable Machine Learning

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
EurekAlert!

Geophysical-machine learning tool for continuous subsurface geomaterials characterization

Researchers utilize 2D electrical resistivity imaging and borehole data to estimate the N60-value of soils with k-means clustering technique Thailand's northern regions, characterized by complex ...
IEEE

Differential Privacy Enabled Robust Asynchronous Federated Multitask Learning: A Multigradient Descent Approach

Abstract: The federated learning (FL) technique can provide a promising solution for the timely training of a deep learning model with the critical requirement of privacy protection. However, the ...