Machine Learning-Based Models Incorporating Social Determinants of Health vs Traditional Models for Predicting In-Hospital Mortality in Patients With Heart Failure.
Sign Up to like & getrecommendations! Published in 2022 at "JAMA cardiology"
DOI: 10.1001/jamacardio.2022.1900
Abstract: Importance Traditional models for predicting in-hospital mortality for patients with heart failure (HF) have used logistic regression and do not account for social determinants of health (SDOH). Objective To develop and validate novel machine learning… read more here.
Keywords: black patients; race; non black; predicting hospital ... See more keywords
Risk models for predicting the health-related quality of life of caregivers of youth with gastrointestinal concerns
Sign Up to like & getrecommendations! Published in 2020 at "Quality of Life Research"
DOI: 10.1007/s11136-020-02601-7
Abstract: To determine the usefulness of cumulative and additive risk models in predicting the healthy-related quality of life (HRQOL) of caregivers of youth with chronic gastrointestinal conditions. 203 caregivers (82.8% mothers; 77.3% white) of youth (M = 11.27… read more here.
Keywords: risk; cumulative risk; quality life; risk models ... See more keywords
Multivariate models for predicting glacier termini
Sign Up to like & getrecommendations! Published in 2017 at "Environmental Earth Sciences"
DOI: 10.1007/s12665-017-7135-2
Abstract: Concerns over the rapid retreat rates of mountain glaciers have been rising as global temperatures have continued to increase. The extent of variation in the retreat of mountain glaciers can provide information about changes to… read more here.
Keywords: mountain glaciers; glacier termini; multivariate models; retreat ... See more keywords
Evaluation of the performance of existing mathematical models predicting enteric methane emissions from ruminants: Animal categories and dietary mitigation strategies
Sign Up to like & getrecommendations! Published in 2019 at "Animal Feed Science and Technology"
DOI: 10.1016/j.anifeedsci.2019.114207
Abstract: The objective of this study was to evaluate the performance of existing models predicting enteric methane (CH4) emissions, using a large database (3183 individual data from 103 in vivo studies on dairy and beef cattle,… read more here.
Keywords: performance existing; performance; rsr; smallest rsr ... See more keywords
Adaptive learning based data-driven models for predicting hourly building energy use
Sign Up to like & getrecommendations! Published in 2018 at "Energy and Buildings"
DOI: 10.1016/j.enbuild.2017.10.054
Abstract: Abstract Accurately predicting energy usage in buildings is of great importance in various efforts on improving building energy efficiencies such as fault detection and diagnostics, building-grid interactions, and building commissioning. Data-driven approach and first-principle approach… read more here.
Keywords: hourly building; energy; data driven; building energy ... See more keywords
Machine Learning Models for Predicting Cytotoxicity of Nanomaterials.
Sign Up to like & getrecommendations! Published in 2022 at "Chemical research in toxicology"
DOI: 10.1021/acs.chemrestox.1c00310
Abstract: The wide application of nanomaterials in consumer and medical products has raised concerns about their potential adverse effects on human health. Thus, more and more biological assessments regarding the toxicity of nanomaterials have been performed.… read more here.
Keywords: cytotoxicity; machine learning; learning models; cytotoxicity nanomaterials ... See more keywords
Machine Learning Models for Predicting Molecular UV-Vis Spectra with Quantum Mechanical Properties
Sign Up to like & getrecommendations! Published in 2023 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c01662
Abstract: Accurate understanding of ultraviolet-visible (UV-vis) spectra is critical for the high-throughput synthesis of compounds for drug discovery. Experimentally determining UV-vis spectra can become expensive when dealing with a large quantity of novel compounds. This provides… read more here.
Keywords: models predicting; learning models; vis spectra; machine learning ... See more keywords
Accurate and efficient machine learning models for predicting hydrogen evolution reaction catalysts based on structural and electronic feature engineering in alloys
Sign Up to like & getrecommendations! Published in 2023 at "Nanoscale"
DOI: 10.1039/d3nr01442h
Abstract: Predictive materials design of high-performance alloy electrocatalysts is a grand challenge in hydrogen production via the water electrolysis. The vast combinatorial space of element substitutions in alloy electrocatalysts offers a... read more here.
Keywords: machine learning; efficient machine; learning models; accurate efficient ... See more keywords
Hierarchical Bayesian models for predicting spatially correlated curves
Sign Up to like & getrecommendations! Published in 2018 at "Statistics"
DOI: 10.1080/02331888.2018.1547905
Abstract: ABSTRACT Functional data analysis has emerged as a new area of statistical research with a wide range of applications. In this paper, we propose novel models based on wavelets for spatially correlated functional data. These… read more here.
Keywords: bayesian models; correlated curves; spatially correlated; predicting spatially ... See more keywords
Application of artificial neural network models for predicting the resilient modulus of recycled aggregates
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Pavement Engineering"
DOI: 10.1080/10298436.2020.1791863
Abstract: In recent years, efforts have been made to utilise construction and demolition (C&D) wastes as an alternative material to natural quarried aggregates in the structural layers of railways and roads.... read more here.
Keywords: neural network; network models; artificial neural; predicting resilient ... See more keywords
Micromechanical models for predicting the mechanical properties of 3D-printed wood/PLA composite materials: A comparison with experimental data
Sign Up to like & getrecommendations! Published in 2021 at "Mechanics of Advanced Materials and Structures"
DOI: 10.1080/15376494.2021.1983901
Abstract: Analytic modeling of 3 D printed natural fiber-reinforced composites is still in its infancy. The existing analytic works on the mechanical properties of these materials seem to be relatively few i... read more here.
Keywords: micromechanical models; properties printed; printed wood; predicting mechanical ... See more keywords