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https://www.readbyqxmd.com/read/28220083/risperidone-effects-on-brain-dynamic-connectivity-a-prospective-resting-state-fmri-study-in-schizophrenia
#1
Kristin K Lottman, Nina V Kraguljac, David M White, Charity J Morgan, Vince D Calhoun, Allison Butt, Adrienne C Lahti
Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated (n = 34), after 1 week (n = 29) and 6 weeks of treatment with risperidone (n = 24), as well as matched controls at baseline (n = 35) and after 6 weeks (n = 19)...
2017: Frontiers in Psychiatry
https://www.readbyqxmd.com/read/28219805/fusion-of-spatial-gray-level-dependency-and-fractal-texture-features-for-the-characterization-of-thyroid-lesions
#2
U Raghavendra, U Rajendra Acharya, Anjan Gudigar, Jen Hong Tan, Hamido Fujita, Yuki Hagiwara, Filippo Molinari, Pailin Kongmebhol, Kwan Hoong Ng
Thyroid is a small gland situated at the anterior side of the neck and one of the largest glands of the endocrine system. The abrupt cell growth or malignancy in the thyroid gland may cause thyroid cancer. Ultrasound images distinctly represent benign and malignant lesions, but accuracy may be poor due to subjective interpretation. Computer Aided Diagnosis (CAD) can minimize the errors created due to subjective interpretation and assists to make fast accurate diagnosis. In this work, fusion of Spatial Gray Level Dependence Features (SGLDF) and fractal textures are used to decipher the intrinsic structure of benign and malignant thyroid lesions...
February 6, 2017: Ultrasonics
https://www.readbyqxmd.com/read/28218214/antidepressant-effects-of-electroconvulsive-therapy-unrelated-to-the-brain-s-functional-network-connectivity-alterations-at-an-individual-level
#3
Guang-Dong Chen, Feng Ji, Gong-Ying Li, Bo-Xuan Lyu, Wei Hu, Chuan-Jun Zhuo
BACKGROUND: Electroconvulsive therapy (ECT) can alleviate the symptoms of treatment-resistant depression (TRD). Functional network connectivity (FNC) is a newly developed method to investigate the brain's functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients...
2017: Chinese Medical Journal
https://www.readbyqxmd.com/read/28217825/preoperative-prediction-of-muscular-invasiveness-of-bladder-cancer-with-radiomic-features-on-conventional-mri-and-its-high-order-derivative-maps
#4
Xiaopan Xu, Yang Liu, Xi Zhang, Qiang Tian, Yuxia Wu, Guopeng Zhang, Jiang Meng, Zengyue Yang, Hongbing Lu
PURPOSE: To determine radiomic features which are capable of reflecting muscular invasiveness of bladder cancer (BC) and propose a non-invasive strategy for the differentiation of muscular invasiveness preoperatively. METHODS: Sixty-eight patients with clinicopathologically confirmed BC were included in this retrospective study. A total of 118 cancerous volumes of interest (VOI) were segmented from patients' T2 weighted MR images (T2WI), including 34 non-muscle invasive bladder carcinomas (NMIBCs, stage <T2) and 84 muscle invasive ones (MIBCs, stage ≥T2)...
February 20, 2017: Abdominal Radiology
https://www.readbyqxmd.com/read/28215473/machine-learning-based-prediction-of-adverse-drug-effects-an-example-of-seizure-inducing-compounds
#5
Mengxuan Gao, Hideyoshi Igata, Aoi Takeuchi, Kaoru Sato, Yuji Ikegaya
Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning...
January 28, 2017: Journal of Pharmacological Sciences
https://www.readbyqxmd.com/read/28214992/data-mining-in-hiv-aids-surveillance-system-application-to-portuguese-data
#6
Alexandra Oliveira, Brígida Mónica Faria, A Rita Gaio, Luís Paulo Reis
The Human Immunodeficiency Virus (HIV) is an infectious agent that attacks the immune system cells. Without a strong immune system, the body becomes very susceptible to serious life threatening opportunistic diseases. In spite of the great progresses on medication and prevention over the last years, HIV infection continues to be a major global public health issue, having claimed more than 36 million lives over the last 35 years since the recognition of the disease. Monitoring, through registries, of HIV-AIDS cases is vital to assess general health care needs and to support long-term health-policy control planning...
April 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28212419/evaluating-the-lexico-grammatical-differences-in-the-writing-of-native-and-non-native-speakers-of-english-in-peer-reviewed-medical-journals-in-the-field-of-pediatric-oncology-creation-of-the-genuine-index-scoring-system
#7
Alberto Alexander Gayle, Motomu Shimaoka
INTRODUCTION: The predominance of English in scientific research has created hurdles for "non-native speakers" of English. Here we present a novel application of native language identification (NLI) for the assessment of medical-scientific writing. For this purpose, we created a novel classification system whereby scoring would be based solely on text features found to be distinctive among native English speakers (NS) within a given context. We dubbed this the "Genuine Index" (GI). METHODOLOGY: This methodology was validated using a small set of journals in the field of pediatric oncology...
2017: PloS One
https://www.readbyqxmd.com/read/28212312/genome-wide-prediction-of-dna-methylation-using-dna-composition-and-sequence-complexity-in-human
#8
Chengchao Wu, Shixin Yao, Xinghao Li, Chujia Chen, Xuehai Hu
DNA methylation plays a significant role in transcriptional regulation by repressing activity. Change of the DNA methylation level is an important factor affecting the expression of target genes and downstream phenotypes. Because current experimental technologies can only assay a small proportion of CpG sites in the human genome, it is urgent to develop reliable computational models for predicting genome-wide DNA methylation. Here, we proposed a novel algorithm that accurately extracted sequence complexity features (seven features) and developed a support-vector-machine-based prediction model with integration of the reported DNA composition features (trinucleotide frequency and GC content, 65 features) by utilizing the methylation profiles of embryonic stem cells in human...
February 16, 2017: International Journal of Molecular Sciences
https://www.readbyqxmd.com/read/28212101/fast-solving-quasi-optimal-ls-s-%C3%A2-vm-based-on-an-extended-candidate-set
#9
Yuefeng Ma, Xun Liang, James T Kwok, Jianping Li, Xiaoping Zhou, Haiyan Zhang
The semisupervised least squares support vector machine (LS-S³VM) is an important enhancement of least squares support vector machines in semisupervised learning. Given that most data collected from the real world are without labels, semisupervised approaches are more applicable than standard supervised approaches. Although a few training methods for LS-S³VM exist, the problem of deriving the optimal decision hyperplane efficiently and effectually has not been solved. In this paper, a fully weighted model of LS-S³VM is proposed, and a simple integer programming (IP) model is introduced through an equivalent transformation to solve the model...
February 14, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28211294/hemopred-a-web-server-for-predicting-the-hemolytic-activity-of-peptides
#10
Thet Su Win, Aijaz Ahmad Malik, Virapong Prachayasittikul, Jarl E S Wikberg, Chanin Nantasenamat, Watshara Shoombuatong
AIM: Toxicity arising from hemolytic activity of peptides hinders its further progress as drug candidates. MATERIALS & METHODS: This study describes a sequence-based predictor based on a random forest classifier using amino acid composition, dipeptide composition and physicochemical descriptors (named HemoPred). RESULTS: This approach could outperform previously reported method and typical classification methods (e.g., support vector machine and decision tree) verified by fivefold cross-validation and external validation with accuracy and Matthews correlation coefficient in excess of 95% and 0...
February 17, 2017: Future Medicinal Chemistry
https://www.readbyqxmd.com/read/28209428/an-artificial-intelligence-based-improved-classification-of-two-phase-flow-patterns-with-feature-extracted-from-acquired-images
#11
C Shanthi, N Pappa
Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are recorded for a period and converted to 2D images for processing...
February 13, 2017: ISA Transactions
https://www.readbyqxmd.com/read/28208285/determining-gender-by-raman-spectroscopy-of-a-bloodstain
#12
Aliaksandra Sikirzhytskaya, Vitali Sikirzhytski, Igor K Lednev
The development of novel methods for forensic science is a constantly growing area of modern analytical chemistry. Raman spectroscopy is one of a few analytical techniques capable of nondestructive and nearly instantaneous analysis of a wide variety of forensic evidence, including body fluid stains, at the scene of a crime. In this proof-of-concept study, Raman microspectroscopy was utilized for gender identification based on dry bloodstains. Raman spectra were acquired in mapping mode from multiple spots on a bloodstain to account for intrinsic sample heterogeneity...
February 7, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/28205576/predicting-antimicrobial-peptides-with-improved-accuracy-by-incorporating-the-compositional-physico-chemical-and-structural-features-into-chou-s-general-pseaac
#13
Prabina Kumar Meher, Tanmaya Kumar Sahu, Varsha Saini, Atmakuri Ramakrishna Rao
Antimicrobial peptides (AMPs) are important components of the innate immune system that have been found to be effective against disease causing pathogens. Identification of AMPs through wet-lab experiment is expensive. Therefore, development of efficient computational tool is essential to identify the best candidate AMP prior to the in vitro experimentation. In this study, we made an attempt to develop a support vector machine (SVM) based computational approach for prediction of AMPs with improved accuracy...
February 13, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28203220/proof-of-concept-of-an-online-emg-based-decoding-of-hand-postures-and-individual-digit-forces-for-prosthetic-hand-control
#14
Alycia Gailey, Panagiotis Artemiadis, Marco Santello
INTRODUCTION: Options currently available to individuals with upper limb loss range from prosthetic hands that can perform many movements, but require more cognitive effort to control, to simpler terminal devices with limited functional abilities. We attempted to address this issue by designing a myoelectric control system to modulate prosthetic hand posture and digit force distribution. METHODS: We recorded surface electromyographic (EMG) signals from five forearm muscles in eight able-bodied subjects while they modulated hand posture and the flexion force distribution of individual fingers...
2017: Frontiers in Neurology
https://www.readbyqxmd.com/read/28203039/quality-assurance-using-outlier-detection-on-an-automatic-segmentation-method-for-the-cerebellar-peduncles
#15
Ke Li, Chuyang Ye, Zhen Yang, Aaron Carass, Sarah H Ying, Jerry L Prince
Cerebellar peduncles (CPs) are white matter tracts connecting the cerebellum to other brain regions. Automatic segmentation methods of the CPs have been proposed for studying their structure and function. Usually the performance of these methods is evaluated by comparing segmentation results with manual delineations (ground truth). However, when a segmentation method is run on new data (for which no ground truth exists) it is highly desirable to efficiently detect and assess algorithm failures so that these cases can be excluded from scientific analysis...
February 27, 2016: Proceedings of SPIE
https://www.readbyqxmd.com/read/28199357/home-detection-of-freezing-of-gait-using-support-vector-machines-through-a-single-waist-worn-triaxial-accelerometer
#16
Daniel Rodríguez-Martín, Albert Samà, Carlos Pérez-López, Andreu Català, Joan M Moreno Arostegui, Joan Cabestany, Àngels Bayés, Sheila Alcaine, Berta Mestre, Anna Prats, M Cruz Crespo, Timothy J Counihan, Patrick Browne, Leo R Quinlan, Gearóid ÓLaighin, Dean Sweeney, Hadas Lewy, Joseph Azuri, Gabriel Vainstein, Roberta Annicchiarico, Alberto Costa, Alejandro Rodríguez-Molinero
Among Parkinson's disease (PD) symptoms, freezing of gait (FoG) is one of the most debilitating. To assess FoG, current clinical practice mostly employs repeated evaluations over weeks and months based on questionnaires, which may not accurately map the severity of this symptom. The use of a non-invasive system to monitor the activities of daily living (ADL) and the PD symptoms experienced by patients throughout the day could provide a more accurate and objective evaluation of FoG in order to better understand the evolution of the disease and allow for a more informed decision-making process in making adjustments to the patient's treatment plan...
2017: PloS One
https://www.readbyqxmd.com/read/28199039/radiomics-assessment-of-bladder-cancer-grade-using-texture-features-from-diffusion-weighted-imaging
#17
Xi Zhang, Xiaopan Xu, Qiang Tian, Baojuan Li, Yuxia Wu, Zengyue Yang, Zhengrong Liang, Yang Liu, Guangbin Cui, Hongbing Lu
PURPOSE: To 1) describe textural features from diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) maps that can distinguish low-grade bladder cancer from high-grade, and 2) propose a radiomics-based strategy for cancer grading using texture features. MATERIALS AND METHODS: In all, 61 patients with bladder cancer (29 in high- and 32 in low-grade groups) were enrolled in this retrospective study. Histogram- and gray-level co-occurrence matrix (GLCM)-based radiomics features were extracted from cancerous volumes of interest (VOIs) on DWI and corresponding ADC maps of each patient acquired from 3...
February 15, 2017: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/28196722/comparison-of-models-for-predicting-the-changes-in-phytoplankton-community-composition-in-the-receiving-water-system-of-an-inter-basin-water-transfer-project
#18
Qinghui Zeng, Yi Liu, Hongtao Zhao, Mingdong Sun, Xuyong Li
Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water transfer projects have rarely been studied. In the present study, we used machine learning models to predict the total algal cell densities and changes in phytoplankton community composition in Miyun reservoir caused by the middle route of the South-to-North Water Transfer Project (SNWTP)...
February 10, 2017: Environmental Pollution
https://www.readbyqxmd.com/read/28194648/epileptic-seizure-classifications-of-single-channel-scalp-eeg-data-using-wavelet-based-features-and-svm
#19
Suparerk Janjarasjitt
In this study, wavelet-based features of single-channel scalp EEGs recorded from subjects with intractable seizure are examined for epileptic seizure classification. The wavelet-based features extracted from scalp EEGs are simply based on detail and approximation coefficients obtained from the discrete wavelet transform. Support vector machine (SVM), one of the most commonly used classifiers, is applied to classify vectors of wavelet-based features of scalp EEGs into either seizure or non-seizure class. In patient-based epileptic seizure classification, a training data set used to train SVM classifiers is composed of wavelet-based features of scalp EEGs corresponding to the first epileptic seizure event...
February 13, 2017: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/28194222/intelligibility-evaluation-of-pathological-speech-through-multigranularity-feature-extraction-and-optimization
#20
Chunying Fang, Haifeng Li, Lin Ma, Mancai Zhang
Pathological speech usually refers to speech distortion resulting from illness or other biological insults. The assessment of pathological speech plays an important role in assisting the experts, while automatic evaluation of speech intelligibility is difficult because it is usually nonstationary and mutational. In this paper, we carry out an independent innovation of feature extraction and reduction, and we describe a multigranularity combined feature scheme which is optimized by the hierarchical visual method...
2017: Computational and Mathematical Methods in Medicine
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