Machine learning elastic constants of multi-component alloys
Sign Up to like & getrecommendations! Published in 2021 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2021.110671
Abstract: Abstract The present manuscript explores application of machine learning methods for determining elastic constants and other derived mechanical properties of multi-component alloys. A number of machine learning models, including linear regression, neural network and random… read more here.
Keywords: multi component; component alloys; predictive performance; elastic constants ... See more keywords
Prediction of illness remission in patients with Obsessive-Compulsive Disorder with supervised machine learning.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of affective disorders"
DOI: 10.1016/j.jad.2021.09.042
Abstract: INTRODUCTION The course of OCD differs widely among OCD patients, varying from chronic symptoms to full remission. No tools for individual prediction of OCD remission are currently available. This study aimed to develop a machine… read more here.
Keywords: machine learning; remission; predictive performance; supervised machine ... See more keywords
Predictive Performance of Four Programmed Cell Death Ligand 1 Assay Systems on Nivolumab Response in Previously Treated Patients with Non–Small Cell Lung Cancer
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Thoracic Oncology"
DOI: 10.1016/j.jtho.2017.11.123
Abstract: Introduction: Nivolumab has demonstrated efficacy against metastatic NSCLC. Four programmed cell death ligand 1 (PD‐L1) immunohistochemistry (IHC) assay systems are available for identification of responders among patients with NSCLC, and these assays show some differing… read more here.
Keywords: four programmed; programmed cell; predictive performance; cell death ... See more keywords
Predictive Nyström method for kernel methods
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2016.12.047
Abstract: Nystrm method is a widely used matrix approximation method for scaling up kernel methods, and existing sampling strategies for Nystrm method are proposed to improve the matrix approximation accuracy, but leaving approximation independent of learning,… read more here.
Keywords: kernel methods; approximation; method; nystrm method ... See more keywords
Predictive performance of international COVID-19 mortality forecasting models
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-22457-w
Abstract: Forecasts and alternative scenarios of COVID-19 mortality have been critical inputs for pandemic response efforts, and decision-makers need information about predictive performance. We screen n = 386 public COVID-19 forecasting models, identifying n = 7 that are global in… read more here.
Keywords: forecasting models; covid mortality; predictive performance; performance ... See more keywords
Evaluation of the predictive performance of the r-k and r-d class estimators
Sign Up to like & getrecommendations! Published in 2017 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2015.1076482
Abstract: ABSTRACT Multiple linear regression models are frequently used in predicting unknown values of the response variable y. In this case, a regression model's ability to produce an adequate prediction equation is of prime importance. This… read more here.
Keywords: class; performance class; predictive performance; class estimators ... See more keywords
Cause-specific mortality prediction in older residents of São Paulo, Brazil: a machine learning approach.
Sign Up to like & getrecommendations! Published in 2021 at "Age and ageing"
DOI: 10.1093/ageing/afab067
Abstract: BACKGROUND Populational ageing has been increasing in a remarkable rate in developing countries. In this scenario, preventive strategies could help to decrease the burden of higher demands for healthcare services. Machine learning algorithms have been… read more here.
Keywords: machine; machine learning; older residents; mortality ... See more keywords
Learning embedding features based on multi-sense-scaled attention architecture to improve the predictive performance of anticancer peptides.
Sign Up to like & getrecommendations! Published in 2021 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab560
Abstract: MOTIVATION Anticancer peptides (ACPs) have recently emerged as effective anticancer drugs in cancer therapy. Machine-learning-based predictors have been developed to identify ACPs and achieve satisfactory performance. However, existing methods suffer from experience-based feature engineering, which… read more here.
Keywords: anticancer peptides; dataset; acpred laf; predictive performance ... See more keywords
2397. Comparing Predictive Performance of INCREMENT Scores on Mortality Among Patients With Carbapenem-Non-Susceptible (CNS) Klebsiella pneumoniae (Kp) and Enterobacter cloacae Complex (Ecc) Bloodstream Infections (BSI) in the Veterans Health Administration (VHA)
Sign Up to like & getrecommendations! Published in 2018 at "Open Forum Infectious Diseases"
DOI: 10.1093/ofid/ofy210.2050
Abstract: Abstract Background INCREMENT is an international collaborative study of BSI caused by extended-spectrum β-lactamase (ESBL) or carbapenemase-producing Enterobacteriaceae (CPE) that has developed and validated predictive models for mortality. Most CNS Enterobacteriaceae BSI in the VHA… read more here.
Keywords: increment; ecc; mortality; vha ... See more keywords
The impact of undersampling on the predictive performance of logistic regression and machine learning algorithms: A simulation study.
Sign Up to like & getrecommendations! Published in 2020 at "Epidemiology"
DOI: 10.1097/ede.0000000000001198
Abstract: e42 | www.epidem.com © 2020 Wolters Kluwer Health, Inc. All rights reserved. To the Editor: Machine learning techniques may improve risk prediction and disease screening. Class imbalance (ratio of noncases to cases > 1) routinely… read more here.
Keywords: logistic regression; machine; predictive performance; machine learning ... See more keywords
Towards Precision Dosing of Clozapine in Schizophrenia: External Evaluation of Population Pharmacokinetic Models and Bayesian Forecasting
Sign Up to like & getrecommendations! Published in 2022 at "Therapeutic Drug Monitoring"
DOI: 10.1097/ftd.0000000000000987
Abstract: Supplemental Digital Content is Available in the Text. Background: Therapeutic drug monitoring and treatment optimization of clozapine are recommended, owing to its narrow therapeutic range and pharmacokinetic (PK) variability. This study aims to assess the… read more here.
Keywords: predictive performance; external evaluation; bayesian forecasting; model ... See more keywords