Researcher finds way to predict whirling disease with almost no data

A study led by a University of Calgary researcher has come up with an AI-based early detection system for river-borne pathogens—including whirling disease in trout and salmon.
EurekAlert!

Machine learning revolutionizes design of green solvents for carbon capture: a new era for ionic liquid development

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) ...
Frontiers

Integrating meteorological and breeding data to predict maize yields using machine learning algorithms

Introduction: Accurate crop yield prediction is vital for ensuring global food security, particularly amid growing environmental challenges such as climate change. Although deep learning (DL) methods ...
IEEE

Rainfall Classification Using Machine Learning Algorithms on Data Mining Platforms

Abstract: Weather conditions directly affect sectors such as agriculture and transport. With climate change, unpredictability is increasing and traditional calculation methods may not be sufficient.
IEEE

Application and Analysis of Machine Learning Based Rainfall Prediction

Rainfall predicting is closely related to people's lives, and improving the accuracy of rainfall prediction is of great importance for people’s life and scientific researches. In this paper we attempt ...
Scientific Research Publishing

Extra Trees Model for Heart Disease Prediction ()

1 Computer Science Department, Babcock University, Ilishan-Remo, Ogun State, Nigeria. 2 Computer Science Department, Adeleke University, Ede, Osun State, Nigeria. 3 Department of Applied Mathematics, ...
BMJ

Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
Frontiers

Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea)

Background: Viral load (VL) suppression is key to ending the global HIV epidemic, and predicting it is critical for healthcare providers and people living with HIV (PLHIV). Traditional research has ...