Recently, a research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a ...

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...

Machine Learning (ML) algorithms have revolutionized various domains by enabling data-driven decision-making and automation.

A machine learning model using routine lab data at 3 months postdiagnosis accurately predicted mortality or liver transplant risk in autoimmune hepatitis.

Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

We developed a classifier to infer acute ischemic stroke severity from Medicare claims using the modified Rankin Scale at discharge. The classifier can be used to improve stroke outcomes research and ...

Abstract: Supercapacitors are considered key components in many industrial and technological applications, due to their high ability to store energy and rapid charging and discharging. In this study, ...

Classic fault detection and classification has some classic problems. It’s reactive, time-consuming to set up, and any product change involves significant man-hours. Even then, it still misses a lot ...

The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ZEF ...