openaccessgovernment

Leveraging machine learning and robust small area estimation methods for stand-level forest inventory

This special report introduces small area estimation (SAE) as a modern approach for producing reliable, stand-level forest inventory information Small area estimation (SAE) is a set of statistical ...
C&EN

A New Pulsed Neutron-Gamma Density Logging Method Based on Gamma-Ray Spectra and Machine Learning

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
Frontiers

Ensemble machine learning for predicting renal function decline in chronic kidney disease: development and external validation

1 Department of Nephrology, the 95th Hospital of Putian in China RongTong Medical Health Corporation, Putian, China 2 Department of Rheumatology and Immunology, the 95th Hospital of Putian in China ...
Frontiers

Leveraging pre-trained embeddings in an ensemble machine learning approach for Arabic sentiment analysis

1 Computer Science Department, Palestine Technical University - Kadoorie, Tulkarm, Palestine 2 Computer Science and Engineering Department, Universidad Carlos III de Madrid, Leganes, Spain ...
Scientific Research Publishing

Ostojic, D., Lalousis, P.A., Donohoe, G. and Morris, D.W. (2024) The Challenges of Using Machine Learning Models in Psychiatric Research and Clinical Practice. European ...

ABSTRACT: Bipolar disorder is a complex psychiatric condition characterized by alternating mood episodes, ranging from depression to mania. Accurate and timely detection of a patient’s current mood ...
IEEE

Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating

Abstract: Ceramic coatings play a vital role in protecting steel components by significantly enhancing their corrosion and wear resistance, thereby extending service life. The performance of these ...
PNAS

LACE-UP: An ensemble machine-learning method for health subtype classification on multidimensional binary data

Cluster analysis can be used on symptom and behavior data to identify groups of similar individuals who may share underlying disease etiology or health risks. However, there are few clustering methods ...