Machine learning for identifying relevant publications in updates of systematic reviews of diagnostic test studies.
Sign Up to like & getrecommendations! Published in 2021 at "Research synthesis methods"
DOI: 10.1002/jrsm.1486
Abstract: BACKGROUND Updating systematic reviews is often a time-consuming process that involves a lot of human effort and is therefore not conducted as often as it should be. The aim of our research project was to… read more here.
Keywords: machine; reviews diagnostic; machine learning; systematic reviews ... See more keywords
In Silico Prediction of Metabolic Epoxidation for Drug-like Molecules via Machine Learning Methods.
Sign Up to like & getrecommendations! Published in 2020 at "Molecular informatics"
DOI: 10.1002/minf.201900178
Abstract: Epoxidation is one of the reactions in drug metabolism. Since epoxide metabolites would bind with proteins or DNA covalently, drugs should avoid epoxidation metabolism in the body. Due to the instability of epoxide, it is… read more here.
Keywords: machine learning; drug; epoxidation; learning methods ... See more keywords
Machine learning methods for generating high dimensional discrete datasets
Sign Up to like & getrecommendations! Published in 2022 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1450
Abstract: The development of platforms and techniques for emerging Big Data and Machine Learning applications requires the availability of real‐life datasets. A possible solution is to synthesize datasets that reflect patterns of real ones using a… read more here.
Keywords: machine; machine learning; methods generating; learning methods ... See more keywords
Epistasis Analysis: Classification Through Machine Learning Methods.
Sign Up to like & getrecommendations! Published in 2021 at "Methods in molecular biology"
DOI: 10.1007/978-1-0716-0947-7_21
Abstract: Complex disease is different from Mendelian disorders. Its development usually involves the interaction of multiple genes or the interaction between genes and the environment (i.e. epistasis). Although the high-throughput sequencing technologies for complex diseases have produced… read more here.
Keywords: machine learning; epistasis analysis; epistasis; learning methods ... See more keywords
Single and Clustered Cervical Cell Classification with Ensemble and Deep Learning Methods
Sign Up to like & getrecommendations! Published in 2020 at "Information Systems Frontiers"
DOI: 10.1007/s10796-020-10028-1
Abstract: Cervical cancer if detected early has an upward of 89% survival rate. The leading tool in identifying cervical cancer in its infancy is the Papanicolaou (Pap smear) test, which since its introduction dropped cervical cancer… read more here.
Keywords: cervical cancer; deep learning; learning methods; pap smear ... See more keywords
Density-based unsupervised ensemble learning methods for time series forecasting of aggregated or clustered electricity consumption
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Intelligent Information Systems"
DOI: 10.1007/s10844-019-00550-3
Abstract: This paper presents a comparison of the impact of various unsupervised ensemble learning methods on electricity load forecasting. The electricity load from consumers is simply aggregated or optimally clustered to more predictable groups by cluster… read more here.
Keywords: time series; electricity; learning methods; unsupervised ensemble ... See more keywords
Feasibility of machine learning methods for predicting hospital emergency room visits for respiratory diseases
Sign Up to like & getrecommendations! Published in 2021 at "Environmental Science and Pollution Research"
DOI: 10.1007/s11356-021-12658-7
Abstract: The prediction of hospital emergency room visits (ERV) for respiratory diseases after the outbreak of PM2.5 is of great importance in terms of public health, medical resource allocation, and policy decision support. Recently, the machine… read more here.
Keywords: machine; machine learning; hospital emergency; respiratory diseases ... See more keywords
Spatio-temporal analysis of forest fire events in the Margalla Hills, Islamabad, Pakistan using socio-economic and environmental variable data with machine learning methods
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Forestry Research"
DOI: 10.1007/s11676-021-01354-4
Abstract: Most forest fires in the Margalla Hills are related to human activities and socioeconomic factors are essential to assess their likelihood of occurrence. This study considers both environmental (altitude, precipitation, forest type, terrain and humidity… read more here.
Keywords: forest fire; forest fires; fire; learning methods ... See more keywords
Unsupervised learning on scientific ocean drilling datasets from the South China Sea
Sign Up to like & getrecommendations! Published in 2018 at "Frontiers of Earth Science"
DOI: 10.1007/s11707-018-0704-1
Abstract: Unsupervised learning methods were applied to explore data patterns in multivariate geophysical datasets collected from ocean floor sediment core samples coming from scientific ocean drilling in the South China Sea. Compared to studies on similar… read more here.
Keywords: south china; china sea; unsupervised learning; learning methods ... 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
Motivational impact of active learning methods in aerospace engineering students
Sign Up to like & getrecommendations! Published in 2019 at "Acta Astronautica"
DOI: 10.1016/j.actaastro.2019.09.026
Abstract: Abstract Motivation is a critical factor in academic performance. In the case of aerospace engineering education, it is particularly necessary due to the difficulty of the subject, so it is essential to use reliable instruments… read more here.
Keywords: engineering; active learning; engineering students; aerospace engineering ... See more keywords