Personalized online ensemble machine learning with applications for dynamic data streams
Sign Up to like & getrecommendations! Published in 2023 at "Statistics in Medicine"
DOI: 10.1002/sim.9655
Abstract: In this work we introduce the personalized online super learner (POSL), an online personalizable ensemble machine learning algorithm for streaming data. POSL optimizes predictions with respect to baseline covariates, so personalization can vary from completely… read more here.
Keywords: time; posl; time series; personalized online ... See more keywords
Ensemble Machine Learning Methods for better Dynamic Assessment of Transformer Status
Sign Up to like & getrecommendations! Published in 2021 at "Journal of The Institution of Engineers (India): Series B"
DOI: 10.1007/s40031-021-00599-1
Abstract: Analyzing dissolved gases in the transformer's mineral oil helps to detect and classify the systemic faults in electric power transformers. Formerly, empirical methods such as Rogers ratio, Duval triangles 1–4–5, and pentagons 1–2 were used… read more here.
Keywords: ensemble machine; transformer; learning methods; power transformers ... See more keywords
Ensemble machine learning models for the detection of energy theft
Sign Up to like & getrecommendations! Published in 2020 at "Electric Power Systems Research"
DOI: 10.1016/j.epsr.2020.106904
Abstract: Abstract Advanced metering infrastructure allows the two-way sharing of information between smart meters and utilities. However, it makes smart grids more vulnerable to cyber-security threats such as energy theft. This study suggests ensemble machine learning… read more here.
Keywords: machine learning; learning models; energy; energy theft ... See more keywords
Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of anxiety disorders"
DOI: 10.1016/j.janxdis.2018.10.004
Abstract: Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. Inexpensive and accurate person-level assessment of PTSD risk after trauma exposure is a critical precursor to large-scale deployment of early interventions that… read more here.
Keywords: machine; machine learning; ensemble machine; screening status ... See more keywords
Flexible Bayesian Ensemble Machine Learning Framework for Predicting Local Ozone Concentrations.
Sign Up to like & getrecommendations! Published in 2022 at "Environmental science & technology"
DOI: 10.1021/acs.est.1c04076
Abstract: 3D-grid-based chemical transport models, such as the Community Multiscale Air Quality (CMAQ) modeling system, have been widely used for predicting concentrations of ambient air pollutants. However, typical horizontal resolutions of nationwide CMAQ simulations (12 ×… read more here.
Keywords: framework; ensemble machine; bayesian ensemble; machine learning ... See more keywords
An Ensemble Machine Learning Model to Enhance Extrapolation Ability of Predicting Coarse Particulate Matter with High Resolutions in China.
Sign Up to like & getrecommendations! Published in 2024 at "Environmental science & technology"
DOI: 10.1021/acs.est.4c08610
Abstract: Accurate exposure assessment is important for conducting PM10-2.5-related epidemiological studies, which have been limited thus far. In this study, we aimed to develop an ensemble machine learning method to estimate PM10-2.5 concentrations in mainland China… read more here.
Keywords: method; pm10; machine learning; extrapolation ... See more keywords
Ensemble machine learning models for sperm quality evaluation concerning success rate of clinical pregnancy in assisted reproductive techniques
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-73326-7
Abstract: This study aimed to investigate the influence of various sperm quality characteristics, including morphology, motility, and count, on the success rates of clinical pregnancy achieved through assisted reproductive technologies (ART) such as in-vitro fertilization (IVF),… read more here.
Keywords: assisted reproductive; clinical pregnancy; success; pregnancy ... See more keywords
Robust diabetic prediction using ensemble machine learning models with synthetic minority over-sampling technique
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-78519-8
Abstract: This paper addresses the pressing issue of diabetes, which is a widespread condition affecting a huge population worldwide. As cells become less responsive to insulin or fail to produce it adequately, blood sugar levels rise.… read more here.
Keywords: prediction using; minority sampling; synthetic minority; machine learning ... See more keywords
Heavy metal adsorption efficiency prediction using biochar properties: a comparative analysis for ensemble machine learning models
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-96271-5
Abstract: The contamination of water and soils with heavy metals poses a significant environmental threat, making the development of effective removal strategies a global priority. Hence, the determination of heavy metals can play an essential role… read more here.
Keywords: adsorption efficiency; ensemble machine; efficiency; heavy metals ... See more keywords
LACE-UP: An ensemble machine-learning method for health subtype classification on multidimensional binary data
Sign Up to like & getrecommendations! Published in 2025 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2423341122
Abstract: Significance 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 for binary data,… read more here.
Keywords: machine learning; lace ensemble; health; ensemble machine ... See more keywords
Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2020.1860145
Abstract: ABSTRACT In this paper, we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree (REPT) as a base classifier with the Bagging (B), Decorate (D), and Random Subspace (RSS) ensemble learning techniques… read more here.
Keywords: machine learning; learning models; error; ensemble machine ... See more keywords