“…Odds ratios (OR) and mean differences (MD) were pooled using the random effects model with the DerSimonian-Laird estimation and displayed on forest plots. The meta-analysis was registered in PROSPERO under number CRD42017077890. …”
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“…We assumed that the home garden owners of the study site are domesticating ethnomedicinal plants which are not easily accessible to them in the wild due to distant forest. This study was planned to explore and document the diversity and population status of ethnomedicinal plants in the home gardens along with its ethnomedicinal use. …”
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“…In the randomly sampled training set (70%), using routinely available triage data as predictors (e.g., demographics, triage vital signs, chief complaints, comorbidities), we developed four machine learning models: Lasso regression, random forest, gradient boosted decision tree, and deep neural network. …”
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“…DESIGN, SETTING, AND PARTICIPANTS: In this exploratory, hypothesis-generating, ad hoc, secondary analysis of data obtained from 9361 participants in SPRINT, a random forest–based analysis was used to identify potential heterogeneous treatment effects using half of the trial data. …”
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“…Identified facilitators of PA were access to safe and engaging outdoor environments such as forests, spacious indoor areas, and adult involvement. …”
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“…A multi-scale object random forest algorithm (MSORF) was used to raise the classification accuracy of the high resolution remote sensing images from 2005 to 2017 in the basin and the multi-scale relationship between the two was discussed using the Pearson correlation analysis method. …”
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“…Forty features were selected according to the ensemble feature selection method, which combined analysis of variance, random forest, and recursive feature elimination. The selected features were further utilized to distinguish IPD patients from HC using the SVM classifier with 10 rounds of 3-fold cross-validation. …”
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“…RESULTS/ANTICIPATED RESULTS: From the 17 exit presentations, six themes were identified: 1) Don’t miss the forest for the trees (x10) – “the KL2 program helps to fill in gaps scholars don’t realize they have – it is about more than just the research project, trust in the process and let the program help keep you on track.” 2) Diversify and keep an open mind (x7) – “focus is important but diversifying research and reorganizing priorities is ok.” 3) Don’t be discouraged by failure (x6) –” perseverance is key, all success comes on the heels of many failures.” 4) Importance of building network inside and outside of Scholar program (x6) – “importance of exploring and establishing collaborations” 5) Learn to say no and yes (x5) – “protect your time but be open to opportunities” 6) Seek advice and criticism but don’t follow blindly (x4) DISCUSSION/SIGNIFICANCE OF IMPACT: The use of exit presentations for graduating KL2 Scholars is a useful tool in transmitting wisdom and enhancing subsequent KL2 cohorts. …”
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“…Unattended livestock were more prone to grey wolf attack during free grazing in forests. Most of the respondents (75.45%) showed aggressive and negative attitudes towards grey wolf. …”
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“…The overall pooled CIN incidence was 13.3% (95% CI: 10.4–17.1). The forest plots showed positive associations between CIN and the presence of hypertension, diabetes mellitus, history of prior myocardial infarction, age, damaged left anterior descending artery, Killip class ≥2, decreased left ventricular ejection fraction, lower estimated glomerular filtration rate, and left ventricular ejection fraction <40%; the odds ratios for these factors were 1.85 (95% CI: 1.57–2.18; p < 0.00001), 1.83 (95% CI: 1.47–2.29; p < 0.00001), 2.14 (95% CI: 1.46–3.14; p < 0.0001), 7.79 (95% CI: 5.24–10.34; p < 0.00001), 1.92 (95% CI: 1.15–3.22; p=0.01), 3.12 (95% CI: 2.21–4.40; p < 0.00001), −6.15 (95% CI: −9.52 to −2.79; p=0.0003), −15.06 (95% CI: −24.75 to −5.36; p=0.002), and 5.53 (95% CI: 1.10–27.95; p=0.04), respectively. …”
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“…A clinical dataset comprising over 5000 actual patients who underwent cardiac surgery in a single center was used to develop the models using logistic regression, artificial neural networks (ANN), support vector machines (SVM), Bayesian belief networks (BBN), naïve Bayesian, random forest, and decision trees. RESULTS: Only 507 out of 5584 patients (11.4%) developed delirium. …”
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“…Both belong to the same alphavirus serocomplex, termed the Semliki Forest serocomplex. The extent of antibody cross-reactivity due to the antigenic relatedness of CHIKV and MAYV in commonly used serologic tests remains unclear. …”
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“…We also recommend further studies to potentially broaden the regulatory definition of Houston Toad habitat beyond the current restrictive view of canopied forest alone. Such studies would need to examine the utility of native grasslands as dispersal corridors/upland habitat for juvenile Houston Toads. …”
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“…METHODS: Three H. erato phyllis females were captured (two from a forest fragment and one from an urban area), and kept individually in open-air insectaries. …”
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“…The majority of these displaced Rohingya settled in informal sites on previously forested land, in areas without basic infrastructure or access to services. …”
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“…The VR app presented users with an omnidirectional video of a peaceful forest environment with a guided mindfulness voiceover that was delivered by a male narrator. …”
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“…Two classification algorithms, support vector machine (SVM) and random forest classifiers, have been deployed. Data from 529 patients were used to train and validate the framework. …”
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“…We then resolve the imbalanced nature of the data through resampling process and a comparative study between the different machine learning (ML) algorithms – Artificial neural network (ANN), Genetic programming (GP), Support vector machines (SVM), Random Forest (RF), Logistic regression (LR) and Decision tree (DT) – was carried out. …”
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“…Cox proportional hazard regression model (Cox model) was used to extract relative genes, and effectiveness of genes was estimated against random forest regression. Finally, risk models were constructed with logistic regression. …”
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