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Toplam kayıt 19, listelenen: 11-19
3-State Protein Secondary Structure Prediction based on SCOPe Classes
(INST TECNOLOGIA PARANARUA PROF ALGACYR MUNHOZ MADER 3775-CIC, 81350-010 CURITIBA-PARANA, BRAZIL, 2021)
Abstract Improving the accuracy of protein secondary structure prediction has been an important task in bioinformatics since it is not only the starting point in obtaining tertiary structure in hierarchical modeling but ...
Correlation of PAPP-A values with maternal characteristics, biochemical and ultrasonographic markers of pregnancy
(MARMARA UNIV, FAC MEDICINEHAYDARPASA, ISTAN, 34668, TURKEY, 2021)
Objective: Our aim is to investigate whether there is a correlation of pregnancy-associated plasma protein A (PAPP-A) values with other variables in pregnancy and maternal characteristics.
Materials and Methods: We ...
Machine-Generated Hierarchical Structure of Human Activities to Reveal How Machines Think
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2021)
Deep-learning based computer vision models have proved themselves to be ground-breaking approaches to human activity recognition (HAR). However, most existing works are dedicated to improve the prediction accuracy through ...
A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization
(AMER MEDICAL ASSOC330 N WABASH AVE, STE 39300, CHICAGO, IL 60611-5885, 2021)
IMPORTANCE Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response ...
Handling incomplete data classification using imputed feature selected bagging (IFBag) method
(IOS PRESSNIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS, 2021)
Almost all real-world datasets contain missing values. Classification of data with missing values can adversely affect the performance of a classifier if not handled correctly. A common approach used for classification ...
Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
The human microbiome has emerged as a central research topic in human biology and biomedicine. Current microbiome studies generate high-throughput omics data across different body sites, populations, and life stages. Many ...
Discovering Potential Taxonomic Biomarkers of Type 2 Diabetes From Human Gut Microbiota via Different Feature Selection Methods
(FRONTIERS MEDIA SAAVENUE DU TRIBUNAL FEDERAL 34, LAUSANNE CH-1015, SWITZERLAND, 2021)
Human gut microbiota is a complex community of organisms including trillions of bacteria. While these microorganisms are considered as essential regulators of our immune system, some of them can cause several diseases. In ...
A noise-aware feature selection approach for classification
(SPRINGERONE NEW YORK PLAZA, SUITE 4600 , NEW YORK, NY 10004, UNITED STATES, 2021)
A noise-aware version of support vector machines is utilized for feature selection in this paper. Combining this method and sequential backward search (SBS), a new algorithm for removing irrelevant features is proposed. ...
Big Data acquired by Internet of Things-enabled industrial multichannel wireless sensors networks for active monitoring and control in the smart grid Industry 4.0
(ELSEVIERRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2021)
Smart Grid Industry 4.0 (SGI4.0) defines a new paradigm to provide high-quality electricity at a low cost by reacting quickly and effectively to changing energy demands in the highly volatile global markets. However, in ...