Models 1. 5-Nearest Neighbor with Dynamic Time Warping (DTW)? 2. 5-Nearest Neighbor with Complexity-Invariant Distance (CID)? 3. Regression on features (Reg) Method 1. 10 fold cross validation 2. Lowest quality training cases duplicated 3. Bayesian approach using Gibbs sampling 4. Model from best algorithm used to classify 90,631 cases 5. Labels correlated with 30-day outcomes (4) Times Series ...

Objective: Accurate image segmentation of the liver is a challenging problem owing to its large shape variability and unclear boundaries. Although applications fully convolutional neural networks (CNNs) have shown groundbreaking results, limited studies focused on performance generalization. In this study, we introduce CNN for abdominal computed tomography (CT) images that focus generalization ...

A two pronged strategy, one involving the Support Vector Machine (SVM) as the classifier and the other including physicochemical properties as additional features, is proposed and implemented here for improved prediction of multi-domains in protein chains. It is experimentally observed to have achieved an accuracy of 76.46 after 25 fold cross validation of results on curated data, derived from ...

This paper describes the HASY dataset of handwritten symbols. HASY is a publicly available, free of charge dataset of single symbols similar to MNIST. It contains 168 233 instances of 369 classes. HASY contains two challenges: A classification challenge with 10 pre-defined folds for 10-fold cross-validation and a verification challenge.

Hold-out and cross-validation are among the most useful methods for model selection and performance assessment of machine learning algorithms. In this paper, we present a computationally efficient algorithm for calculating the hold-out performance for sparse regularized least-squares (RLS) in case the method is already trained with the whole training set. The computational complexity of perform...

Objective: There are abundant mentions of clinical conditions, anatomical sites, medications and procedures in clinical documents. This paper describes use of a cascade of machine learners to automatically extract mentions of named entities about disorders from clinical notes. Tasks: A Conditional Random Field (CRF) machine learner has been used for named entity recognition and to capture more ...

COVID-19 turned out to be an infectious and life-threatening viral disease, its swift overwhelming spread has become one of the greatest challenges for world. As yet, no satisfactory vaccine or medication been developed that could guarantee mitigation, though several efforts trials are underway. Countries around globe striving overcome while they finding ways early detection timely treatment. I...

Abstract Support vector classification (SVC) is a classical and well-performed learning method for problems. A regularization parameter, which significantly affects the performance, has to be chosen this usually done by cross-validation procedure. In paper, we reformulate hyperparameter selection problem support as bilevel optimization in upper-level minimizes average number of misclassified da...

Since the microbiome has a significant impact on human health and disease, microbe-disease associations can be utilized as a valuable resource for understanding disease pathogenesis and promoting disease diagnosis and prognosis. Accordingly, it is necessary for researchers to achieve a comprehensive and deep understanding of the associations between microbes and diseases. Nevertheless, to date,...

a reliable quantitative structure retention relationship (qsrr) study has been evaluated to predict the retention indices (ris) of a broad spectrum of compounds, namely 118 non-linear, cyclic and heterocyclic terpenoids (both saturated and unsaturated), on an hp-5ms fused silica column. a principal component analysis showed that seven compounds lay outside of the main cluster. after elimination...