LIVIVO - Search results -

Search results

Result 1 - 10 of total 44

Search options

Article: Artificial Intelligence-Based Family Health Education Public Service System.

Zhao, Jingyi / Fu, Guifang

2022 Volume 13, Page(s) 898107

Abstract: Family health education is a must for every family, so that children can be taught how to protect their own health. However, in this era of artificial intelligence, many technical operations based on artificial intelligence are born, so the purpose of ... ...

Abstract	Family health education is a must for every family, so that children can be taught how to protect their own health. However, in this era of artificial intelligence, many technical operations based on artificial intelligence are born, so the purpose of this study is to apply artificial intelligence technology to family health education. This paper proposes a fusion of artificial intelligence and IoT technologies. Based on the characteristics of artificial intelligence technology, it combines ZigBee technology and RFID technology in the Internet of Things technology to design an artificial intelligence-based service system. Then it designs the theme of family health education by conducting a questionnaire on students' family education and analyzing the results of the questionnaire. And it designs database and performance analysis experiments to improve the artificial intelligence-based family health education public service system designed in this paper. Finally, a comparative experiment between the family health education public service system based on artificial intelligence and the traditional health education method will be carried out. The experimental results show that the family health education public service system based on artificial intelligence has improved by 21.74% compared with the traditional family health education method; compared with the traditional family health education method, the health education effect of the family health education public service system based on artificial intelligence has increased by 13.89%.
Language	English
Publishing date	2022-05-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2563826-9
ISSN	1664-1078
ISSN	1664-1078
DOI	10.3389/fpsyg.2022.898107
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article ; Online: A mathematical view for ordinary differential equation models: Comment on "Epigenetic game theory: How to compute the epigenetic control of maternal-to-zygotic transition" by Qian Wang et al.

Fu, Guifang

Physics of life reviews

2017 Volume 20, Page(s) 138–139

MeSH term(s)	Animals ; Biological Evolution ; Epigenomics ; Game Theory ; Humans ; Zygote
Language	English
Publishing date	2017
Publishing country	Netherlands
Document type	Journal Article ; Comment
ZDB-ID	2148883-6
ISSN	1873-1457 ; 1571-0645
ISSN (online)	1873-1457
ISSN	1571-0645
DOI	10.1016/j.plrev.2017.02.001
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Statistical Learning Methods Applicable to Genome-Wide Association Studies on Unbalanced Case-Control Disease Data.

Dai, Xiaotian / Fu, Guifang / Zhao, Shaofei / Zeng, Yifei

Genes

2021 Volume 12, Issue 5

Abstract: Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health ... ...

Abstract	Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health records have enabled the collection of thousands of phenotypes from large cohorts, in particular for diseases with low prevalence. The unbalanced binary traits pose serious challenges to traditional statistical methods in terms of both genomic selection and disease prediction. For example, the well-established linear mixed models (LMM) yield inflated type I error rates in the presence of unbalanced case-control ratios. In this article, we review multiple statistical approaches that have been developed to overcome the inaccuracy caused by the unbalanced case-control ratio, with the advantages and limitations of each approach commented. In addition, we also explore the potential for applying several powerful and popular state-of-the-art machine-learning approaches, which have not been applied to the GWAS field yet. This review paves the way for better analysis and understanding of the unbalanced case-control disease data in GWAS.
MeSH term(s)	Case-Control Studies ; Genome/genetics ; Genome-Wide Association Study/methods ; Genomics/methods ; Humans ; Linear Models ; Machine Learning ; Phenotype
Language	English
Publishing date	2021-05-13
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2527218-4
ISSN	2073-4425 ; 2073-4425
ISSN (online)	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12050736
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Functional random forests for curve response.

Fu, Guifang / Dai, Xiaotian / Liang, Yeheng

Scientific reports

2021 Volume 11, Issue 1, Page(s) 24159

Abstract: The rapid advancement of functional data in various application fields has increased the demand for advanced statistical approaches that can incorporate complex structures and nonlinear associations. In this article, we propose a novel functional random ... ...

Abstract	The rapid advancement of functional data in various application fields has increased the demand for advanced statistical approaches that can incorporate complex structures and nonlinear associations. In this article, we propose a novel functional random forests (FunFor) approach to model the functional data response that is densely and regularly measured, as an extension of the landmark work of Breiman, who introduced traditional random forests for a univariate response. The FunFor approach is able to predict curve responses for new observations and selects important variables from a large set of scalar predictors. The FunFor approach inherits the efficiency of the traditional random forest approach in detecting complex relationships, including nonlinear and high-order interactions. Additionally, it is a non-parametric approach without the imposition of parametric and distributional assumptions. Eight simulation settings and one real-data analysis consistently demonstrate the excellent performance of the FunFor approach in various scenarios. In particular, FunFor successfully ranks the true predictors as the most important variables, while achieving the most robust variable sections and the smallest prediction errors when comparing it with three other relevant approaches. Although motivated by a biological leaf shape data analysis, the proposed FunFor approach has great potential to be widely applied in various fields due to its minimal requirement on tuning parameters and its distribution-free and model-free nature. An R package named 'FunFor', implementing the FunFor approach, is available at GitHub.
Language	English
Publishing date	2021-12-17
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-02265-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: Statistical Learning Methods Applicable to Genome-Wide Association Studies on Unbalanced Case-Control Disease Data

Dai, Xiaotian / Fu, Guifang / Zhao, Shaofei / Zeng, Yifei

Genes. 2021 May 13, v. 12, no. 5

2021

Abstract	Despite the fact that imbalance between case and control groups is prevalent in genome-wide association studies (GWAS), it is often overlooked. This imbalance is getting more significant and urgent as the rapid growth of biobanks and electronic health records have enabled the collection of thousands of phenotypes from large cohorts, in particular for diseases with low prevalence. The unbalanced binary traits pose serious challenges to traditional statistical methods in terms of both genomic selection and disease prediction. For example, the well-established linear mixed models (LMM) yield inflated type I error rates in the presence of unbalanced case-control ratios. In this article, we review multiple statistical approaches that have been developed to overcome the inaccuracy caused by the unbalanced case-control ratio, with the advantages and limitations of each approach commented. In addition, we also explore the potential for applying several powerful and popular state-of-the-art machine-learning approaches, which have not been applied to the GWAS field yet. This review paves the way for better analysis and understanding of the unbalanced case-control disease data in GWAS.
Keywords	artificial intelligence ; marker-assisted selection ; prediction ; telemedicine
Language	English
Dates of publication	2021-0513
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	2527218-4
ISSN	2073-4425
ISSN	2073-4425
DOI	10.3390/genes12050736
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Article ; Online: Detecting PCOS susceptibility loci from genome-wide association studies via iterative trend correlation based feature screening.

Dai, Xiaotian / Fu, Guifang / Reese, Randall

BMC bioinformatics

2020 Volume 21, Issue 1, Page(s) 177

Abstract: Background: Feature screening plays a critical role in handling ultrahigh dimensional data analyses when the number of features exponentially exceeds the number of observations. It is increasingly common in biomedical research to have case-control ( ... ...

Abstract	Background: Feature screening plays a critical role in handling ultrahigh dimensional data analyses when the number of features exponentially exceeds the number of observations. It is increasingly common in biomedical research to have case-control (binary) response and an extremely large-scale categorical features. However, the approach considering such data types is limited in extant literature. In this article, we propose a new feature screening approach based on the iterative trend correlation (ITC-SIS, for short) to detect important susceptibility loci that are associated with the polycystic ovary syndrome (PCOS) affection status by screening 731,442 SNP features that were collected from the genome-wide association studies. Results: We prove that the trend correlation based screening approach satisfies the theoretical strong screening consistency property under a set of reasonable conditions, which provides an appealing theoretical support for its outperformance. We demonstrate that the finite sample performance of ITC-SIS is accurate and fast through various simulation designs. Conclusion: ITC-SIS serves as a good alternative method to detect disease susceptibility loci for clinic genomic data.
MeSH term(s)	Case-Control Studies ; Female ; Genetic Predisposition to Disease ; Genome ; Genome-Wide Association Study/methods ; Humans ; Polycystic Ovary Syndrome/diagnosis ; Polycystic Ovary Syndrome/genetics
Language	English
Publishing date	2020-05-04
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-020-3492-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: An adaptive threshold determination method of feature screening for genomic selection.

Fu, Guifang / Wang, Gang / Dai, Xiaotian

BMC bioinformatics

2017 Volume 18, Issue 1, Page(s) 212

Abstract: Background: Although the dimension of the entire genome can be extremely large, only a parsimonious set of influential SNPs are correlated with a particular complex trait and are important to the prediction of the trait. Efficiently and accurately ... ...

Abstract	Background: Although the dimension of the entire genome can be extremely large, only a parsimonious set of influential SNPs are correlated with a particular complex trait and are important to the prediction of the trait. Efficiently and accurately selecting these influential SNPs from millions of candidates is in high demand, but poses challenges. We propose a backward elimination iterative distance correlation (BE-IDC) procedure to select the smallest subset of SNPs that guarantees sufficient prediction accuracy, while also solving the unclear threshold issue for traditional feature screening approaches. Results: Verified through six simulations, the adaptive threshold estimated by the BE-IDC performed uniformly better than fixed threshold methods that have been used in the current literature. We also applied BE-IDC to an Arabidopsis thaliana genome-wide data. Out of 216,130 SNPs, BE-IDC selected four influential SNPs, and confirmed the same FRIGIDA gene that was reported by two other traditional methods. Conclusions: BE-IDC accommodates both the prediction accuracy and the computational speed that are highly demanded in the genomic selection.
MeSH term(s)	Arabidopsis/genetics ; Arabidopsis Proteins/genetics ; Computer Simulation ; Genome, Plant ; Genome-Wide Association Study ; Genomics ; Models, Genetic ; Phenotype ; Plant Breeding ; Polymorphism, Single Nucleotide
Chemical Substances	Arabidopsis Proteins ; FRI protein, Arabidopsis
Language	English
Publishing date	2017-04-12
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-017-1617-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: A Bivariate Hypothesis Testing Approach for Mapping the Trait-Influential Gene.

Saunders, Garrett / Fu, Guifang / Stevens, John R

Scientific reports

2017 Volume 7, Issue 1, Page(s) 12798

Abstract: The linkage disequilibrium (LD) based quantitative trait loci (QTL) model involves two indispensable hypothesis tests: the test of whether or not a QTL exists, and the test of the LD strength between the QTaL and the observed marker. The advantage of ... ...

Abstract	The linkage disequilibrium (LD) based quantitative trait loci (QTL) model involves two indispensable hypothesis tests: the test of whether or not a QTL exists, and the test of the LD strength between the QTaL and the observed marker. The advantage of this two-test framework is to test whether there is an influential QTL around the observed marker instead of just having a QTL by random chance. There exist unsolved, open statistical questions about the inaccurate asymptotic distributions of the test statistics. We propose a bivariate null kernel (BNK) hypothesis testing method, which characterizes the joint distribution of the two test statistics in two-dimensional space. The power of this BNK approach is verified by three different simulation designs and one whole genome dataset. It solves a few challenging open statistical questions, closely separates the confounding between 'linkage' and 'QTL effect', makes a fine genome division, provides a comprehensive understanding of the entire genome, overcomes limitations of traditional QTL approaches, and connects traditional QTL mapping with the newest genotyping technologies. The proposed approach contributes to both the genetics literature and the statistics literature, and has a potential to be extended to broader fields where a bivariate test is needed.
MeSH term(s)	Chromosome Mapping ; Computer Simulation ; Data Analysis ; Genome-Wide Association Study ; Linkage Disequilibrium/genetics ; Models, Genetic ; Quantitative Trait Loci/genetics
Language	English
Publishing date	2017-10-09
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-017-10177-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

Fu, Guifang / Dai, Xiaotian / Symanzik, Jürgen / Bushman, Shaun

The New phytologist

2016 Volume 213, Issue 1, Page(s) 455–469

Abstract: Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and ... ...

Abstract	Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures.
MeSH term(s)	Algorithms ; Computer Simulation ; Gene-Environment Interaction ; Genes, Plant ; Genetic Pleiotropy ; Image Processing, Computer-Assisted ; Linkage Disequilibrium/genetics ; Models, Genetic ; Plant Leaves/anatomy & histology ; Plant Leaves/genetics ; Populus/anatomy & histology ; Populus/genetics ; Principal Component Analysis ; Satellite Communications ; Trees/anatomy & histology ; Trees/genetics
Language	English
Publishing date	2016-09-21
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	208885-x
ISSN	1469-8137 ; 0028-646X
ISSN (online)	1469-8137
ISSN	0028-646X
DOI	10.1111/nph.14131
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Bonn / Germany

Z 868: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Article ; Online: Mapping morphological shape as a high-dimensional functional curve.

Fu, Guifang / Huang, Mian / Bo, Wenhao / Hao, Han / Wu, Rongling

Briefings in bioinformatics

2017 Volume 19, Issue 3, Page(s) 461–471

Abstract: Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, ... ...

Abstract	Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, statistically modeling the high-dimensional shape and meticulously locating shape quantitative trait loci (QTL) affect the progress of this research. In this article, we propose a novel integrated framework that incorporates shape analysis, statistical curve modeling and genetic mapping to detect significant QTLs regulating variation of biological shape traits. After quantifying morphological shape via a radius centroid contour approach, each shape, as a phenotype, was characterized as a high-dimensional curve, varying as angle θ runs clockwise with the first point starting from angle zero. We then modeled the dynamic trajectories of three mean curves and variation patterns as functions of θ. Our framework led to the detection of a few significant QTLs regulating the variation of leaf shape collected from a natural population of poplar, Populus szechuanica var tibetica. This population, distributed at altitudes 2000-4500 m above sea level, is an evolutionarily important plant species. This is the first work in the quantitative genetic shape mapping area that emphasizes a sense of 'function' instead of decomposing the shape into a few discrete principal components, as the majority of shape studies do.
MeSH term(s)	Chromosome Mapping/methods ; Chromosomes, Plant ; Computer Simulation ; Genes, Plant ; Models, Statistical ; Phenotype ; Plant Leaves/anatomy & histology ; Plant Leaves/genetics ; Populus/anatomy & histology ; Populus/genetics ; Quantitative Trait Loci
Language	English
Publishing date	2017-01-06
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbw111
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 6262: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

To top

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito