Selection (genetic algorithm)
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Thrombectomy for Stroke at 6 to 16 Hours with Selection by Perfusion Imaging Open
Endovascular thrombectomy for ischemic stroke 6 to 16 hours after a patient was last known to be well plus standard medical therapy resulted in better functional outcomes than standard medical therapy alone among patients with proximal mid…
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Unobservable Selection and Coefficient Stability: Theory and Evidence Open
A common approach to evaluating robustness to omitted variable bias is to observe coefficient movements after inclusion of controls. This is informative only if selection on observables is informative about selection on unobservables. Alth…
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The Delphi Technique: Making Sense of Consensus Open
The Delphi technique is a widely used and accepted method for gathering data from respondents within their domain of expertise. The technique is designed as a group communication process which aims to achieve a convergence of opinion on a …
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Adaptation and Natural Selection: A Critique of Some Current Evolutionary Thought Open
Biological evolution is a fact-but the many conflicting theories of evolution remain controversial even today. When Adaptation and Natural Selection was first published in 1966, it struck a powerful blow against those who argued for the co…
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CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens Open
CRISPOR.org is a web tool for genome editing experiments with the CRISPR-Cas9 system. It finds guide RNAs in an input sequence and ranks them according to different scores that evaluate potential off-targets in the genome of interest and p…
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Feature Selection Open
Feature selection, as a data preprocessing strategy, has been proven to be effective and efficient in preparing data (especially high-dimensional data) for various data-mining and machine-learning problems. The objectives of feature select…
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An Overview of Overfitting and its Solutions Open
Overfitting is a fundamental issue in supervised machine learning which prevents us from perfectly generalizing the models to well fit observed data on training data, as well as unseen data on testing set. Because of the presence of noise,…
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Methodological quality and synthesis of case series and case reports Open
Case reports and case series are uncontrolled study designs known for increased risk of bias but have profoundly influenced the medical literature and continue to advance our knowledge. In this guide, we present a framework for appraisal, …
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BERTScore: Evaluating Text Generation with BERT Open
We propose BERTScore, an automatic evaluation metric for text generation. Analogously to common metrics, BERTScore computes a similarity score for each token in the candidate sentence with each token in the reference sentence. However, ins…
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ModelTest-NG: A New and Scalable Tool for the Selection of DNA and Protein Evolutionary Models Open
ModelTest-NG is a reimplementation from scratch of jModelTest and ProtTest, two popular tools for selecting the best-fit nucleotide and amino acid substitution models, respectively. ModelTest-NG is one to two orders of magnitude faster tha…
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SMS: Smart Model Selection in PhyML Open
Model selection using likelihood-based criteria (e.g., AIC) is one of the first steps in phylogenetic analysis. One must select both a substitution matrix and a model for rates across sites. A simple method is to test all combinations and …
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Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR Open
Background The success of the CRISPR/Cas9 genome editing technique depends on the choice of the guide RNA sequence, which is facilitated by various websites. Despite the importance and popularity of these algorithms, it is unclear to which…
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E-Commerce Promotional Products Selection Using SWARA and TOPSIS Open
This research aims to select products that will be used for promotion on e-commerce platforms. The increasing use of e-commerce has led to a high level of competition in the e-commerce field. The company strives to maintain the quality of …
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Estimation of clinical trial success rates and related parameters Open
Previous estimates of drug development success rates rely on relatively small samples from databases curated by the pharmaceutical industry and are subject to potential selection biases. Using a sample of 406 038 entries of clinical trial …
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Insights into Molecular Classifications of Triple-Negative Breast Cancer: Improving Patient Selection for Treatment Open
Triple-negative breast cancer (TNBC) remains the most challenging breast cancer subtype to treat. To date, therapies directed to specific molecular targets have rarely achieved clinically meaningful improvements in outcomes of patients wit…
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Recruiting the ABCD sample: Design considerations and procedures Open
The ABCD study is a new and ongoing project of very substantial size and scale involving 21 data acquisition sites. It aims to recruit 11,500 children and follow them for ten years with extensive assessments at multiple timepoints. To deli…
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Tools and techniques for solvent selection: green solvent selection guides Open
Driven by legislation and evolving attitudes towards environmental issues, establishing green solvents for extractions, separations, formulations and reaction chemistry has become an increasingly important area of research. Several general…
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Robustness of linear mixed‐effects models to violations of distributional assumptions Open
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make sever…
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Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Open
With the broader and highly successful usage of machine learning in industry\nand the sciences, there has been a growing demand for Explainable AI.\nInterpretability and explanation methods for gaining a better understanding\nabout the pro…
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Electrolyte selection for supercapacitive devices: a critical review Open
The supercapacitive charge storage as a function of electrolyte factors are critically reviewed.
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Phylogenetic network analysis of SARS-CoV-2 genomes Open
Significance This is a phylogenetic network of SARS-CoV-2 genomes sampled from across the world. These genomes are closely related and under evolutionary selection in their human hosts, sometimes with parallel evolution events, that is, th…
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Particle Swarm Optimization: A Comprehensive Survey Open
Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature. Although the original PSO has shown good optimization performance, it still severely suffers from premature convergence. As a resu…
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Environmental factors influencing the development and spread of antibiotic resistance Open
Antibiotic resistance and its wider implications present us with a growing healthcare crisis. Recent research points to the environment as an important component for the transmission of resistant bacteria and in the emergence of resistant …
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Person Re-identification: Past, Present and Future Open
Person re-identification (re-ID) has become increasingly popular in the community due to its application and research significance. It aims at spotting a person of interest in other cameras. In the early days, hand-crafted algorithms and s…
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Optimized libraries for CRISPR-Cas9 genetic screens with multiple modalities Open
The creation of genome-wide libraries for CRISPR knockout (CRISPRko), interference (CRISPRi), and activation (CRISPRa) has enabled the systematic interrogation of gene function. Here, we show that our recently-described CRISPRko library (B…
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A Simple New Approach to Variable Selection in Regression, with Application to Genetic Fine Mapping Open
Summary We introduce a simple new approach to variable selection in linear regression, with a particular focus on quantifying uncertainty in which variables should be selected. The approach is based on a new model—the ‘sum of single effect…
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Variable selection strategies and its importance in clinical prediction modelling Open
Clinical prediction models are used frequently in clinical practice to identify patients who are at risk of developing an adverse outcome so that preventive measures can be initiated. A prediction model can be developed in a number of ways…
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ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs Open
How to model a pair of sentences is a critical issue in many NLP tasks such as answer selection (AS), paraphrase identification (PI) and textual entailment (TE). Most prior work (i) deals with one individual task by fine-tuning a specific …
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kuenm: an R package for detailed development of ecological niche models using Maxent Open
Background Ecological niche modeling is a set of analytical tools with applications in diverse disciplines, yet creating these models rigorously is now a challenging task. The calibration phase of these models is critical, but despite rece…
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Collider scope: when selection bias can substantially influence observed associations Open
Large-scale cross-sectional and cohort studies have transformed our understanding of the genetic and environmental determinants of health outcomes. However, the representativeness of these samples may be limited-either through selection in…