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A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction
2020
Scientific Reports
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methods when modelling high-dimensional, heterogeneous, clinical data. ...
This work compares the performance and stability of ten machine learning algorithms, combined with eight feature selection methods, capable of performing survival analysis of high-dimensional, heterogeneous ...
As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. ...
doi:10.1038/s41598-020-77220-w
pmid:33230128
fatcat:vjo33snfzfajbmaehcrrpte3yy
Trace Ratio Linear Discriminant Analysis for Medical Diagnosis: A Case Study of Dementia
2013
IEEE Signal Processing Letters
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This novel method can be integrated with advanced missing value imputation method and utilized for the analysis of the nonlinear datasets in many real-world medical diagnosis problems. ...
In this paper, we introduce trace ratio linear discriminant analysis (TR-LDA) for dementia diagnosis. An improved ITR algorithm (iITR) is developed to solve the TR-LDA problem. ...
Besser for database support. The NACC database was supported by NIA Grant UO1 AG016976. ...
doi:10.1109/lsp.2013.2250281
pmid:24077217
pmcid:PMC3784002
fatcat:gj2y3vnrxjdn7n2wwopejazb6q
Dementia Patient Segmentation Using EMR Data Visualization: A Design Study
2019
International Journal of Environmental Research and Public Health
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It facilitates the investigation of disease patterns and efficient treatment via collaboration with data scientists. (2) Methods: In this study, we present multidimensional visual tools for the analysis ...
based on EMR data via visual analysis. ...
For these reasons, the medical community has called for a need to develop a simplified model for dementia diagnosis to reduce expenses, based on patient data analysis. ...
doi:10.3390/ijerph16183438
pmid:31527556
pmcid:PMC6765847
fatcat:hpd2h2k4wbedlelwccghjylqcq
Automated identification of dementia using medical imaging: a survey from a pattern classification perspective
2015
Brain Informatics
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, and four categories of classifiers, including the linear discriminant analysis, Bayes classifiers, support vector machines, and artificial neural networks. ...
We also compare the reported performance of many recently published dementia identification algorithms. ...
[54] used a high-dimensional template to wrap original data and employed a watershed method to get the robust features. ...
doi:10.1007/s40708-015-0027-x
pmid:27747596
pmcid:PMC4883162
fatcat:yefc226j4za75afkkkolg4m5n4
Cooperative Correlational and Discriminative Ensemble Classifier Learning for Early Dementia Diagnosis Using Morphological Brain Multiplexes
2018
IEEE Access
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One potential factor for their reduced accuracies was the addition of principle component analysis (PCA) as neither method can directly handle high-dimensional data. ...
In particular, for ECFS method, we applied PCA to the deep convolutional multiplexes as it was unable to handle high dimensional data. ...
doi:10.1109/access.2018.2863657
fatcat:cuqkferfzbgn7itr4eelg5mkgm
Individual Subject Classification of Mixed Dementia from Pure Subcortical Vascular Dementia Based on Subcortical Shape Analysis
2013
PLoS ONE
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Identifying mixed dementia from SVaD is important because potential amyloid-targeted therapies may be effective for treatment in mixed dementia. ...
An incremental learning method using hippocampal and amygdalar shape distinguishes mixed dementia from pure SVaD. ...
Our classification method provides a useful tool for classifying mixed dementia from pure SVaD with relatively high accuracy, which has clinical implications for diagnosis and treatment. ...
doi:10.1371/journal.pone.0075602
pmid:24130724
pmcid:PMC3794958
fatcat:phb2ezzezjaurm5qcwn63pons4
Role of EEG as Biomarker in the Early Detection and Classification of Dementia
2014
The Scientific World Journal
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This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis. ...
The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression ...
These methods are well-established methods for dimensionality reduction. PCA is a widely used method to avoid the redundancy because of high-dimensional data [125] [126] [127] . ...
doi:10.1155/2014/906038
pmid:25093211
pmcid:PMC4100295
fatcat:l5qz7chnzzgizaoxjpvshuyqr4
Three-dimensional stereotactic surface projection in the statistical analysis of single photon emission computed tomography data for distinguishing between Alzheimer's disease and depression
2017
World Journal of Psychiatry
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Of these, Factor 1 could be interpreted as favouring a tendency for AD, Factor 2 as favouring a tendency for pseudo-dementia, and Factor 3 as favouring a depressive tendency. ...
Factor analysis identified three significant factors. ...
In the analysis of the score for each factor for each type, Type A (true AD) had high scores for Factor 1 (tendency for AD), type B (pseudo-dementia) had high scores for Factor 2 (tendency for pseudo-dementia ...
doi:10.5498/wjp.v7.i2.121
pmid:28713690
pmcid:PMC5491477
fatcat:jyqwu35tpvdlrjpx6hk327owqi
Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer's Disease Based on Deep Learning and Hybrid Methods
2021
Electronics
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For the OASIS dataset, we balanced the dataset, replaced the missing values, and applied the t-Distributed Stochastic Neighbour Embedding algorithm (t-SNE) to represent the high-dimensional data in the ...
All of the machine learning algorithms, namely, Support Vector Machine (SVM), Decision Tree, Random Forest and K Nearest Neighbours (KNN), achieved high performance for diagnosing dementia. ...
Acknowledgments: We would like to acknowledge the Scientific Research Deanship at the University of Ha'il, Saudi Arabia, for funding this research. ...
doi:10.3390/electronics10222860
fatcat:2vgkbev6ifdp7adweaoesanr3a
Guidelines for reporting methodological challenges and evaluating potential bias in dementia research
2015
Alzheimer's & Dementia
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months, years, or even decades; (4) time-varying measurements; and (5) high-dimensional data. ...
We present findings from a large scientific working group on research methods for clinical and population studies of dementia, which identified five categories of methodological challenges as follows: ...
High-dimensional data analysis generates multiple statistical comparisons/tests potentially addressed by various statistical corrections (family-wise error and false discovery). ...
doi:10.1016/j.jalz.2015.06.1885
pmid:26397878
pmcid:PMC4655106
fatcat:ptlg2oi6jfa6bpfxouc4zi2yby
Full exploitation of high dimensionality in brain imaging: The JPND working group statement and findings
2019
Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
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The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. ...
For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. ...
Future directions: In this report, we propose a framework for analyzing high-dimensional data. Still, this is only an initial step. ...
doi:10.1016/j.dadm.2019.02.003
pmid:30976649
pmcid:PMC6441785
fatcat:gcfwt7hjijcedl2m5duecwx5gy
Usefulness of 3-dimensional stereotactic surface projection FDG PET images for the diagnosis of dementia
2016
Medicine
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of dementia compared with the visual method alone, except for AD/MCI specificity and FTD sensitivity. ...
The addition of 3D-SSP images to visual analysis helped to discriminate different types of dementia in FDG PET scans, by correcting misdiagnoses and enhancing diagnostic confidence in the correct diagnosis ...
Acknowledgments The authors thank statistical advice for this manuscript from our statistician (Professor Myung Hwan Na, Department of statistics, Chonnam National University, Korea). ...
doi:10.1097/md.0000000000005622
pmid:27930593
pmcid:PMC5266065
fatcat:42mykwde45dspfrg44ci43nnha
Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients using Primary Care Electronic Health Records
2020
IEEE Journal of Translational Engineering in Health and Medicine
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Such data however, provides a challenging problem space for traditional statistics and machine learning due to high dimensionality and sparse data elements. ...
The identification of at risk individuals allows for preventative measures to alleviate said strain. Electronic health records provide opportunity for big data analysis to address such applications. ...
To address such challenges, this article proposes a novel methodology for predicting hospital admission for individuals with dementia whilst simultaneously performing feature reduction on a sparse, high-dimensional ...
doi:10.1109/jtehm.2020.3040236
pmid:33354439
pmcid:PMC7737850
fatcat:yke3szmmzff6hg54ngwu6p7koa
Dementia: Continuum or distinct entity?
2010
Psychology and Aging
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Subjecting these data to taxometric analysis using mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and latent mode factor analysis (L-Mode) produced results more consistent with dementia ...
as a dimensional (lying along a continuum) than categorical (representing a distinct entity) construct. ...
Latent mode factor analysis (L-Mode) data curve for the four dementia indicators (dark solid line) in comparison to simulated taxonic (lighter solid line) and dimensional data (lighter dotted line) with ...
doi:10.1037/a0018167
pmid:20677881
pmcid:PMC2943994
fatcat:qyx3rgw4vzcatbcacr4s3uqdri
Re-assessing the dimensional structure of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): empirical evidence for a shortened Brazilian version
2015
BMC Geriatrics
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A Confirmatory Factor Analysis (CFA) first tested the originally proposed one-dimensional structure comprised of 26 items. ...
Methods: The sample comprised 652 elderly and their informants, either attending a geriatric service of a public university clinic or enrolled in a health care provider database in Rio de Janeiro, Brazil ...
As for the dimensional structure of the instrument, most authors suggested a one-dimensional solution, through studies using different statistical methods [8-12, 23, 24] . ...
doi:10.1186/s12877-015-0098-9
pmid:26227264
pmcid:PMC4521482
fatcat:kpat6t6jw5bojgzcbbamzmlh4u
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