“…We used stacking ensemble learning to combine logistic regression (LR), random forest (RF), artificial neural network (ANN), support vector machine (SVM), and k-nearest neighbors (KNN) models. …”
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“…METHODS: We used UK primary care EHR data from individuals aged ≥30 years without known AF in the CPRD-GOLD dataset (Jan 2, 1998, Nov 30, 2018), randomly divided into training (80%) and testing (20%) datasets. We trained a random forest classifier using age, sex, ethnicity and comorbidities (FIND-AF). …”
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“…The analysis also showed that they are typically associated with forest habitats, and their distribution is strongly influenced by climate, which is confirmed by our data on their ability to grow at different temperatures. …”
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“…Specimens were sampled from some cases and sent to laboratories for influenza nucleic acid testing. Random forest was used to establish an influenza estimation model based on the influenza-positive rate and the percentage of ILIs among outpatients. …”
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“…Molecular signatures and candidate markers for PCC were developed using gene set enrichment analysis (GSEA) and machine learning, including random forest (RF) and support vector machine (SVM) methods. …”
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“…Different association methods (random-forest, generalized linear models, and the Spearman correlation index) support the number of contigs, the coverage, and fragmentation as the assembly parameters that most affect the estimation of the alpha diversity. …”
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“…The genus Otidea is one of the more conspicuous members of the Pyronemataceae, with high species diversity in hemiboreal and boreal forests. The genus is morphologically coherent and in previous higher-level multi-gene analyses it formed a highly supported monophyletic group. …”
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“…Fowler Jr., Pfizer, Novartis, Galderma, Novadigm, Durata, Debiopharm, Genentech, Achaogen, Affinium, Medicines Co., Cerexa, Tetraphase, Trius, MedImmune, Bayer, Theravance, Cubist, Basilea, Affinergy, Janssen, xBiotech, Contrafect: Consultant, Consulting fee; NIH, Basilea, MedImmune, Cerexa/Forest/Actavis/Allergan, Pfizer, Advanced Liquid Logics, Theravance, Novartis, Cubist/Merck; Medical Biosurfaces; Locus; Affinergy; Contrafect; Karius: Grant Investigator, Research grant; Green Cross, Cubist, Cerexa, Durata, Theravance; Debiopharm: Consultant, Consulting fee; UpToDate: author on several chapters, Royalties…”
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“…The variables of age, spherical equivalent (SE), and annual progression rate were used to develop an algorithm to predict SE and onset of high myopia (SE ≤ −6.0 dioptres) up to 10 years in the future. Random forest machine learning was used for algorithm training and validation. …”
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“…Using all attributes (age, sex, involved vessel segment, and angiographic features affecting the myocardial territory and stenosis degree), the ML classifiers (L2 penalized logistic regression, support vector machine, and random forest) predicted an FFR < 0.80 with an accuracy of approximately 80% (area under the curve [AUC] = 0.84–0.87, 95% confidence intervals 0.71–0.94) in the test set, which was greater than that of diameter stenosis (DS) > 53% (66%, AUC = 0.71, 95% confidence intervals 0.65–0.78). …”
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“…OBJECTIVES/SPECIFIC AIMS: Wake Forest Baptist Health (WFBH) is an Academic Learning Healthcare System (aLHS) serving 24 counties in North Carolina and Virginia. …”
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“…The distribution and density of ticks along a gradient of wooded habitats, as well as biotic variables, such as the presence and abundance of their principal domestic (livestock) and wild hosts (small mammals), were measured from forest cores and edges to more or less isolated hedges, all bordering meadows. …”
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“…METHODS: Ecological sampling for documenting bird species richness was conducted from November 2015 to May 2017 in three transects that included agroforestry systems, forests, and fallow agricultural land. The method of counting by fixed radius points at 16 points within the study systems was used. …”
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“…To investigate the validity of CT quantification in the management of COVID-19, we built random forest (RF) models for the purpose of classification and regression to assess the disease severity (Moderate, Severe, and Critical) and to predict the need and length of ICU stay, the duration of oxygen inhalation, hospitalization, sputum NAT-positive, and patient prognosis. …”
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“…The above immunologic coclusters achieved an area under the receiver operating characteristic curve of 0.801 (95% confidence interval, 0.764–0.838), and its combined model with the coagulation and fibrinolysis indices (prothrombin time, D-dimer) achieved an area under the receiver operating characteristic curve of 0.815 (95% confidence interval, 0.779–0.851) using the random forest regression model to predict severe or critical illness. …”
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“…Fowler, Jr., MD, MHS, Achaogen (Consultant)Actavis (Grant/Research Support)Advanced Liquid Logics (Grant/Research Support)Affinergy (Consultant, Research Grant or Support)Affinium (Consultant)Allergan (Grant/Research Support)Ampliphi Biosciences (Consultant)Basilea (Consultant, Research Grant or Support)Bayer (Consultant)C3J (Consultant)Cerexa (Consultant, Research Grant or Support)Contrafect (Consultant, Research Grant or Support)Cubist (Grant/Research Support)Debiopharm (Consultant)Destiny (Consultant)Durata (Consultant)Forest (Grant/Research Support)Genentech (Consultant, Research Grant or Support)Integrated Biotherapeutics (Consultant)Janssen (Consultant, Research Grant or Support)Karius (Grant/Research Support)Locus (Grant/Research Support)Medical Biosurfaces (Grant/Research Support)Medicines Co. …”
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“…[Image: see text] Table 1: Antimicrobial use for all patients and by advance directive group [Image: see text] Figure 2. Forest plot of model estimates, represented as incidence rate ratios (IRR) with 95% confidence intervals (CI), for associations between POLST antimicrobial specifications completed at least 30 days before death and inpatient antibiotic days of therapy (DOT) in the 30 days before death. …”
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“…Associations with CV death were evaluated by Random Survival Forest (RF) and Cox regression analyses. Both cohorts had the same median age (65 years) and 20% smokers, while there were slight differences in male sex (82% and 76%), hypertension (70% and 78%), and diabetes (39% and 30%) in the respective STABILITY and LURIC cohorts. …”
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“…Main outcome measures: The forest plots allowed an overall relative risk and percentage risk to be calculated from all the risk data gathered from the studies. …”
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“…We used the χ (2) test that goes with the forest plot and computed the I (2) statistic to assess heterogeneity. …”
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