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https://www.readbyqxmd.com/read/29452575/a-machine-learning-approach-to-detect-changes-in-gait-parameters-following-a-fatiguing-occupational-task
#1
Amir Baghdadi, Fadel M Megahed, Ehsan T Esfahani, Lora A Cavuoto
The purpose of this study is to provide a method for classifying non-fatigued versus fatigued states following manual material handling. A method of template matching pattern recognition for feature extraction (1$ Recognizer) along with the support vector machine (SVM) model for classification were applied on the kinematics of gait cycles segmented by our stepwise search-based segmentation algorithm. A single inertial measurement unit (IMU) on the ankle was used, providing a minimally intrusive and inexpensive tool for monitoring...
February 16, 2018: Ergonomics
https://www.readbyqxmd.com/read/29451998/predicting-the-integrated-visual-field-with-wide-scan-optical-coherence-tomography-in-glaucoma-patients
#2
Masaaki Yoshida, Shiho Kunimatsu-Sanuki, Kazuko Omodaka, Toru Nakazawa
PURPOSE: This study aimed to calculate a predicted integrated visual field (IVF) based on predicted monocular visual fields (MVFs) derived, with a new method, from wide-scan optical coherence tomography (OCT) data. MATERIALS AND METHODS: Visual field testing used the central (6 × 4) 24 points of the Humphrey Field Analyzer 24-2 program. OCT scans of a corresponding retinal area, centered on the fovea, were divided into a 6 × 4 grid. The thickness of the macular retinal nerve fiber layer (mRNFL), ganglion cell layer + inner plexiform layer (GCIPL), and mRNFL + GCIPL (GCC) was measured in each grid area...
February 16, 2018: Current Eye Research
https://www.readbyqxmd.com/read/29451280/a-remote-computing-based-point-of-care-colorimetric-detection-system-with-a-smartphone-under-complex-ambient-light-conditions
#3
Xu Bao, Shu Jiang, Yun Wang, Miao Yu, Juan Han
Smartphone-based colorimetric detection has been one of the most commonly used techniques for point-of-care detection in recent years. However, there are two defects in the current detection system. One is the need of a light-tight box to isolate the impact of ambient light, and the other is the increased calculation with the number of probes. In this paper, a colorimetric detection system was coupled with a new color calibration method for detection under complex ambient light conditions. A 3 × 4 colorimetric probe array was used to display the color changes of different analytes...
February 16, 2018: Analyst
https://www.readbyqxmd.com/read/29447214/high-efficiency-classification-of-children-with-autism-spectrum-disorder
#4
Genyuan Li, Olivia Lee, Herschel Rabitz
Autism spectrum disorder (ASD) is a wide-ranging collection of developmental diseases with varying symptoms and degrees of disability. Currently, ASD is diagnosed mainly with psychometric tools, often unable to provide an early and reliable diagnosis. Recently, biochemical methods are being explored as a means to meet the latter need. For example, an increased predisposition to ASD has been associated with abnormalities of metabolites in folate-dependent one carbon metabolism (FOCM) and transsulfuration (TS)...
2018: PloS One
https://www.readbyqxmd.com/read/29445429/classification-of-mri-and-psychological-testing-data-based-on-support-vector-machine
#5
Wenlu Yang, Xinyun Chen, David S Cohen, Eric R Rosin, Arthur W Toga, Paul M Thompson, Xudong Huang
Alzheimer's disease (AD) is a progressive, and often fatal, brain disease that causes neurodegeneration, resulting in memory loss as well as other cognitive and behavioral problems. Here, we propose a novel multimodal method combining independent components from MRI measures and clinical assessments to distinguish Alzheimer's patients or mild cognitive impairment (MCI) subjects from healthy elderly controls. 70 AD subjects (mean age: 77.15 ± 6.2 years), 98 MCI subjects (mean age: 76.91 ± 5.7 years), and 150 HC subjects (mean age: 75...
December 2017: International Journal of Clinical and Experimental Medicine
https://www.readbyqxmd.com/read/29443925/pclass-protein-quaternary-structure-classification-by-using-bootstrapping-strategy-as-model-selection
#6
Chi-Chou Huang, Chi-Chang Chang, Chi-Wei Chen, Shao-Yu Ho, Hsung-Pin Chang, Yen-Wei Chu
Protein quaternary structure complex is also known as a multimer, which plays an important role in a cell. The dimer structure of transcription factors is involved in gene regulation, but the trimer structure of virus-infection-associated glycoproteins is related to the human immunodeficiency virus. The classification of the protein quaternary structure complex for the post-genome era of proteomics research will be of great help. Classification systems among protein quaternary structures have not been widely developed...
February 14, 2018: Genes
https://www.readbyqxmd.com/read/29439448/rapid-screening-of-cadmium-in-rice-and-identification-of-geographical-origins-by-spectral-method
#7
Fang Li, Jihua Wang, Li Xu, Songxue Wang, Minghui Zhou, Jingwei Yin, Anxiang Lu
The accuracy, repeatability and detection limits of the energy-dispersive X-ray fluorescence (XRF) spectrometer used in this study were tested to verify its suitability for rapid screening of cadmium in samples. Concentrations of cadmium in rice grain samples were tested by the XRF spectrometer. The results showed that the apparatus had good precision around the national limit value (0.2 mg/kg). Raman spectroscopy has been analyzed in the discrimination of rice grain samples from different geographical origins within China...
February 11, 2018: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/29439345/joint-assessment-of-quantitative-18f-florbetapir-and-18f-fdg-regional-uptake-using-baseline-data-from-the-adni
#8
Fayçal Ben Bouallègue, Denis Mariano-Goulart, Pierre Payoux
Joint analysis of amyloid and metabolic PET patterns across healthy, mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects was performed using baseline 18F-florbetapir and 18F-FDG PET of 684 subjects from the ADNI (251 normal, 204 stable MCI, 85 AD converters, and 144 AD). Correlation between regional amyloid and metabolic uptake was measured and predictive value of PET profile regarding AD conversion in cognitively impaired subjects was assessed using survival analysis and support vector machine classification (SVM)...
2018: Journal of Alzheimer's Disease: JAD
https://www.readbyqxmd.com/read/29437268/using-support-vector-machine-analysis-to-assess-partinmr-a-new-prediction-model-for-organ-confined-prostate-cancer
#9
Jing Wang, Chen-Jiang Wu, Mei-Ling Bao, Jing Zhang, Hai-Bin Shi, Yu-Dong Zhang
BACKGROUND: Partin tables represent the most widely used predictive tool for prostate cancer stage at prostatectomy but with potential limitations. PURPOSE: To develop a new PartinMR model for organ-confined prostate cancer (OCPCA) by incorporating Partin table and mp-MRI with a support vector machine (SVM) analysis. STUDY TYPE: Retrospective. POPULATION: In all, 541 patients with biopsy-confirmed prostate cancer underwent mp-MRI...
February 13, 2018: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/29436887/machine-learning-in-autistic-spectrum-disorder-behavioral-research-a-review-and-ways-forward
#10
Fadi Thabtah
Autistic Spectrum Disorder (ASD) is a mental disorder that retards acquisition of linguistic, communication, cognitive, and social skills and abilities. Despite being diagnosed with ASD, some individuals exhibit outstanding scholastic, non-academic, and artistic capabilities, in such cases posing a challenging task for scientists to provide answers. In the last few years, ASD has been investigated by social and computational intelligence scientists utilizing advanced technologies such as machine learning to improve diagnostic timing, precision, and quality...
February 13, 2018: Informatics for Health & Social Care
https://www.readbyqxmd.com/read/29436619/a-six-long-non-coding-rna-signature-predicts-prognosis-in-melanoma-patients
#11
Shuocheng Yang, Jianguo Xu, Xuan Zeng
The aim of this study was to identify long non-coding RNAs (lncRNAs) which may prove useful for risk-classifying patients with melanoma. For this purpose, based on a dataset from The Cancer Genome Atlas (TCGA), we selected and analyzed samples from melanoma stages I, II, III and IV, from which differentially expressed lncRNAs were identified. The lncRNAs were classified using two-way hierarchical clustering analysis and analysis of support vector machine (SVM), followed by Kaplan-Meier survival analysis. The prognostic capacity of the signature was verified on an independent dataset...
February 7, 2018: International Journal of Oncology
https://www.readbyqxmd.com/read/29436168/feasibility-study-of-individualized-optimal-positioning-selection-for-left-sided-whole-breast-radiotherapy-dibh-or-prone
#12
Hui Lin, Tianyu Liu, Chengyu Shi, Saskia Petillion, Isabelle Kindts, Caroline Weltens, Tom Depuydt, Yulin Song, Ziad Saleh, Xie George Xu, Xiaoli Tang
The deep inspiration breath hold (DIBH) and prone (P) position are two common heart-sparing techniques for external-beam radiation treatment of left-sided breast cancer patients. Clinicians select the position that is deemed to be better for tissue sparing based on their experience. This approach, however, is not always optimum and consistent. In response to this, we develop a quantitative tool that predicts the optimal positioning for the sake of organs at risk (OAR) sparing. Sixteen left-sided breast cancer patients were considered in the study, each received CT scans in the supine free breathing, supine DIBH, and prone positions...
February 13, 2018: Journal of Applied Clinical Medical Physics
https://www.readbyqxmd.com/read/29434722/analysis-of-long-non-coding-rna-expression-profiles-identifies-functional-lncrnas-associated-with-the-progression-of-acute-coronary-syndromes
#13
Yingjie Lu, Xiangwei Meng, Lifeng Wang, Xiaoyun Wang
It has been demonstrated that long non-coding RNAs (lncRNAs) are important in the gene regulatory network and their dysregulated expression has been implicated in cardiovascular disease. However, little is known regarding lncRNA expression patterns and their function in the progression of acute coronary syndromes (ACSs). In the present study, the expression profiles of lncRNAs from 52 patients with ACS were analyzed by re-annotating existing microarray data. The lncRNA expression profiles in the two distinct clinical entities of ACS, myocardial infarction (MI) and unstable angina (UA), were examined...
February 2018: Experimental and Therapeutic Medicine
https://www.readbyqxmd.com/read/29433432/predictors-of-breast-cancer-cell-types-and-their-prognostic-power-in-breast-cancer-patients
#14
Fan Wang, Zachariah Dohogne, Jin Yang, Yu Liu, Benjamin Soibam
BACKGROUND: Comprehensive understanding of intratumor heterogeneity requires identification of molecular markers, which are capable of differentiating different subpopulations and which also have clinical significance. One important tool that has been addressing this issue is single cell RNA-Sequencing (scRNASeq) that allows the quantification of expression profiles of transcripts in individual cells in a population of cancer cells. Using the expression profiles from scRNASeq, current studies conduct analysis to group cells into different subpopulations using clustering algorithms...
February 13, 2018: BMC Genomics
https://www.readbyqxmd.com/read/29432992/merging-weighted-svms-for-parallel-incremental-learning
#15
Lei Zhu, Kazushi Ikeda, Shaoning Pang, Tao Ban, Abdolhossein Sarrafzadeh
Parallel incremental learning is an effective approach for rapidly processing large scale data streams, where parallel and incremental learning are often treated as two separate problems and solved one after another. Incremental learning can be implemented by merging knowledge from incoming data and parallel learning can be performed by merging knowledge from simultaneous learners. We propose to simultaneously solve the two learning problems with a single process of knowledge merging, and we propose parallel incremental wESVM (weighted Extreme Support Vector Machine) to do so...
February 2, 2018: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/29430935/the-effect-of-glioblastoma-heterogeneity-on-survival-stratification-a-multimodal-mr-imaging-texture-analysis
#16
Yang Liu, Xi Zhang, Na Feng, Lulu Yin, Yalong He, Xiaopan Xu, Hongbing Lu
Background Quantitative evaluation of the effect of glioblastoma (GBM) heterogeneity on survival stratification would be critical for the diagnosis, treatment decision, and follow-up management. Purpose To evaluate the effect of GBM heterogeneity on survival stratification, using texture analysis on multimodal magnetic resonance (MR) imaging. Material and Methods A total of 119 GBM patients (65 in long-term and 54 in short-term survival group, separated by overall survival of 12 months) were selected from the Cancer Genome Atlas, who underwent the T1-weighted (T1W) contrast-enhanced (CE), T1W, T2-weighted (T2W), and FLAIR sequences...
January 1, 2018: Acta Radiologica
https://www.readbyqxmd.com/read/29430478/use-of-clinical-mri-maximum-intensity-projections-for-improved-breast-lesion-classification-with-deep-convolutional-neural-networks
#17
Natalia Antropova, Hiroyuki Abe, Maryellen L Giger
Deep learning methods have been shown to improve breast cancer diagnostic and prognostic decisions based on selected slices of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). However, incorporation of volumetric and temporal components into DCE-MRIs has not been well studied. We propose maximum intensity projection (MIP) images of subtraction MRI as a way to simultaneously include four-dimensional (4-D) images into lesion classification using convolutional neural networks (CNN). The study was performed on a dataset of 690 cases...
January 2018: Journal of Medical Imaging
https://www.readbyqxmd.com/read/29430027/principal-weighted-support-vector-machines-for-sufficient-dimension-reduction-in-binary-classification
#18
Seung Jun Shin, Yichao Wu, Hao Helen Zhang, Yufeng Liu
Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods may work poorly for binary classification. For example, sliced inverse regression (Li, 1991) can estimate at most one direction if the response is binary. In this paper we propose principal weighted support vector machines, a unified framework for linear and nonlinear sufficient dimension reduction in binary classification. Its asymptotic properties are studied, and an efficient computing algorithm is proposed...
March 2017: Biometrika
https://www.readbyqxmd.com/read/29428411/a-sensor-based-wrist-pulse-signal-processing-and-lung-cancer-recognition
#19
Zhichao Zhang, Yuan Zhang, Houbing Song, Lina Yao, Anton Kos
Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals...
February 8, 2018: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29428061/classification-of-cancer-cells-using-computational-analysis-of-dynamic-morphology
#20
Mohammad R Hasan, Naeemul Hassan, Rayan Khan, Young-Tae Kim, Samir M Iqbal
BACKGROUND AND OBJECTIVE: Detection of metastatic tumor cells is important for early diagnosis and staging of cancer. However, such cells are exceedingly difficult to detect from blood or biopsy samples at the disease onset. It is reported that cancer cells, and especially metastatic tumor cells, show very distinctive morphological behavior compared to their healthy counterparts on aptamer functionalized substrates. The ability to quickly analyze the data and quantify the cell morphology for an instant real-time feedback can certainly contribute to early cancer diagnosis...
March 2018: Computer Methods and Programs in Biomedicine
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