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https://www.readbyqxmd.com/read/29029305/large-scale-automated-sleep-staging
#1
Haoqi Sun, Jian Jia, Balaji Goparaju, Guang-Bin Huang, Olga Sourina, Matt Travis Bianchi, M Brandon Westover
Study Objectives: Automated sleep staging has been previously limited by a combination of clinical and physiological heterogeneity. Both factors are in principle addressable with large data sets that enable robust calibration. However, the impact of sample size remains uncertain. The objectives are to investigate the extent to which machine learning methods can approximate the performance of human scorers when supplied with sufficient training cases and to investigate how staging performance depends on the number of training patients, contextual information, model complexity, and imbalance between sleep stage proportions...
September 26, 2017: Sleep
https://www.readbyqxmd.com/read/29029029/a-manifesto-for-cardiovascular-imaging-addressing-the-human-factor
#2
Alan G Fraser
Our use of modern cardiovascular imaging tools has not kept pace with their technological development. Diagnostic errors are common but seldom investigated systematically. Rather than more impressive pictures, our main goal should be more precise tests of function which we select because their appropriate use has therapeutic implications which in turn have a beneficial impact on morbidity or mortality. We should practise analytical thinking, use checklists to avoid diagnostic pitfalls, and apply strategies that will reduce biases and avoid overdiagnosis...
September 28, 2017: European Heart Journal Cardiovascular Imaging
https://www.readbyqxmd.com/read/29028926/structure-based-prediction-of-protein-peptide-binding-regions-using-random-forest
#3
Ghazaleh Taherzadeh, Yaoqi Zhou, Alan Wee-Chung Liew, Yuedong Yang
Motivation: Protein-peptide interactions are one of the most important biological interactions and play crucial role in many diseases including cancer. Therefore, knowledge of these interactions provides invaluable insights into all cellular processes, functional mechanisms, and drug discovery. Protein-peptide interactions can be analyzed by studying the structures of protein-peptide complexes. However, only a small portion has known complex structures and experimental determination of protein-peptide interaction is costly and inefficient...
September 26, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028911/genome-wide-pre-mirna-discovery-from-few-labeled-examples
#4
C Yones, G Stegmayer, D H Milone
Motivation: Although many machine learning techniques have been proposed for distinguishing miRNA hairpins from other stem-loop sequences, most of the current methods use supervised learning, which requires a very good set of positive and negative examples. Those methods have important practical limitations when they have to be applied to a real prediction task. First, there is the challenge of dealing with a scarce number of positive (well-known) pre-miRNA examples. Secondly, it is very difficult to build a good set of negative examples for representing the full spectrum of non-miRNA sequences...
September 25, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028697/machine-learning-and-sepsis-on-the-road-to-revolution
#5
Vincent X Liu, Allan J Walkey
No abstract text is available yet for this article.
November 2017: Critical Care Medicine
https://www.readbyqxmd.com/read/29028652/novel-dry-lab-training-method-for-totally-endoscopic-coronary-anastomosis-a-pilot-study
#6
Kosuke Ujihira, Akira Yamada
OBJECTIVE: We describe our original dry-lab training system for nonrobotic and beating heart endoscopic coronary artery anastomosis. METHODS: All the materials used for this training were commercially available. We selected a boxed machine, which can produce pulsatile movements of artificial vessels, and on its roof, we installed a two-dimensional home video camera and a monitor. A multiple-holed plate was placed in front of the machine, and through these holes, a trainee inserted endoscopic surgical instruments and anastomosed the artificial vessels by running fashion while watching the monitor...
October 13, 2017: Innovations: Technology and Techniques in Cardiothoracic and Vascular Surgery
https://www.readbyqxmd.com/read/29028263/epigenomic-annotation-based-interpretation-of-genomic-data-from-enrichment-analysis-to-machine-learning
#7
Mikhail G Dozmorov
Motivation: One of the goals of functional genomics is to understand the regulatory implications of experimentally obtained genomic regions of interest (ROIs). Most sequencing technologies now generate ROIs distributed across the whole genome. The interpretation of these genome-wide ROIs represents a challenge as the majority of them lie outside of functionally well-defined protein coding regions. Recent efforts by the members of the International Human Epigenome Consortium have generated volumes of functional/regulatory data (reference epigenomic datasets), effectively annotating the genome with epigenomic properties...
October 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29028213/classification-of-imbalanced-data-by-oversampling-in-kernel-space-of-support-vector-machines
#8
Josey Mathew, Chee Khiang Pang, Ming Luo, Weng Hoe Leong
Historical data sets for fault stage diagnosis in industrial machines are often imbalanced and consist of multiple categories or classes. Learning discriminative models from such data sets is challenging due to the lack of representative data and the bias of traditional classifiers toward the majority class. Sampling methods like synthetic minority oversampling technique (SMOTE) have been traditionally used for such problems to artificially balance the data set before being trained by a classifier. This paper proposes a weighted kernel-based SMOTE (WK-SMOTE) that overcomes the limitation of SMOTE for nonlinear problems by oversampling in the feature space of support vector machine (SVM) classifier...
October 10, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/29028135/predicting-episodic-and-spatial-memory-performance-from-hippocampal-resting-state-functional-connectivity-evidence-for-an-anterior-posterior-division-of-function
#9
Jonas Persson, Eva Stening, Kristin Nordin, Hedvig Söderlund
fMRI studies have identified distinct resting-state functional connectivity (RSFC) networks associated with the anterior and posterior hippocampus. However, the functional relevance of these two networks is still largely unknown. Hippocampal lesion studies and task-related fMRI point to a role for the anterior hippocampus in non-spatial episodic memory and the posterior hippocampus in spatial memory. We used Relevance Vector Regression (RVR), a machine-learning method that enables predictions of continuous outcome measures from multivariate patterns of brain imaging data, to test the hypothesis that patterns of whole-brain RSFC associated with the anterior hippocampus predict episodic memory performance, while patterns of whole-brain RSFC associated with the posterior hippocampus predict spatial memory performance...
October 13, 2017: Hippocampus
https://www.readbyqxmd.com/read/29027789/integrated-bacterial-identification-and-antimicrobial-susceptibility-testing-using-pcr-and-high-resolution-melt
#10
Pornpat Athamanolap, Kuangwen Hsieh, Liben Chen, Samuel Yang, Tza-Huei Wang
Accurate and timely diagnostics are critical for managing bacterial infections. The current gold standard, culture-based diagnostics can provide clinicians with comprehensive diagnostic information including bacterial identity and antimicrobial susceptibility, but they often require several days of turnaround time, which leads to compromised clinical outcome and promotes the spread of antibiotic resistance. Nucleic acid amplification tests such as PCR have significantly accelerated the detection of specific bacteria, but generally lack the capacities for broad-based bacterial identification or antimicrobial susceptibility testing...
October 13, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/29027463/machine-learning-based-olfactometer-prediction-of-odor-perception-from-physicochemical-features-of-odorant-molecules
#11
Liang Shang, Chuanjun Liu, Yoichi Tomiura, Kenshi Hayashi
Gas chromatography-olfactometry (GC-O) has been used in various fields as a valuable method to identify odor-active components from a complex mixture. Since human assessors are employed as a detector to obtain the olfactory perception of separated odorants, the GC-O technique is limited by its subjectivity, variability, and high cost of the trained panelist. Here, we present a proof-of-concept model by which odor information can be obtained by machine-learning based prediction from molecular parameters (MPs) of odorant molecules...
October 13, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/29027093/long-term-prognostic-value-of-coronary-computed-tomography-angiography
#12
REVIEW
Takor B Arrey-Mbi, Seth M Klusewitz, Todd C Villines
Coronary CT angiography (CTA) is a highly accurate test for the diagnosis of coronary artery disease (CAD), with its use guided by numerous contemporary appropriate use criteria and clinical guidelines. Unique among non-invasive tests for CAD, coronary CTA provides direct visualization of coronary atherosclerosis for the assessment of angiographic stenosis, as well as validated measures of plaque vulnerability. Long-term studies now clearly demonstrate that the absence of CAD on coronary CTA identifies a patient that is at very low risk for future cardiovascular events...
October 12, 2017: Current Treatment Options in Cardiovascular Medicine
https://www.readbyqxmd.com/read/29026108/rifs-a-randomly-restarted-incremental-feature-selection-algorithm
#13
Yuting Ye, Ruochi Zhang, Weiwei Zheng, Shuai Liu, Fengfeng Zhou
The advent of big data era has imposed both running time and learning efficiency challenges for the machine learning researchers. Biomedical OMIC research is one of these big data areas and has changed the biomedical research drastically. But the high cost of data production and difficulty in participant recruitment introduce the paradigm of "large p small n" into the biomedical research. Feature selection is usually employed to reduce the high number of biomedical features, so that a stable data-independent classification or regression model may be achieved...
October 12, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29025029/ct-coronary-imaging-a-fast-evolving-world
#14
Prabhakar Rajiah, Suhny Abbara
Computed tomography (CT) has become an important modality in the evaluation of coronary artery disease (CAD). The tremendous technological advances in CT in the last two decades has made it possible to obtain high quality images of coronary arteries with high spatial and temporal resolutions. Multiple trials have confirmed the accuracy of CT compared to invasive catheter angiography. CT is also able to evaluate beyond the lumen in characterizing and quantifying atherosclerotic plaques, including evaluation of high risk features...
September 4, 2017: QJM: Monthly Journal of the Association of Physicians
https://www.readbyqxmd.com/read/29023548/comparison-of-six-electromyography-acquisition-setups-on-hand-movement-classification-tasks
#15
Stefano Pizzolato, Luca Tagliapietra, Matteo Cognolato, Monica Reggiani, Henning Müller, Manfredo Atzori
Hand prostheses controlled by surface electromyography are promising due to the non-invasive approach and the control capabilities offered by machine learning. Nevertheless, dexterous prostheses are still scarcely spread due to control difficulties, low robustness and often prohibitive costs. Several sEMG acquisition setups are now available, ranging in terms of costs between a few hundred and several thousand dollars. The objective of this paper is the relative comparison of six acquisition setups on an identical hand movement classification task, in order to help the researchers to choose the proper acquisition setup for their requirements...
2017: PloS One
https://www.readbyqxmd.com/read/29022863/next-generation-sequencing-revealed-divergence-in-deletions-of-the-pres-region-in-the-hbv-genome-between-different-hbv-related-liver-diseases
#16
Jian'an Jia, Xiaotao Liang, Shipeng Chen, Hui Wang, Huiming Li, Meng Fang, Xin Bai, Ziyi Wang, Mengmeng Wang, Shanfeng Zhu, Fengzhu Sun, Chunfang Gao
In order to investigate if deletion patterns of the preS region can predict liver disease advancement, the preS region of the hepatitis B virus (HBV) genome in 45 chronic hepatitis B (CHB) and 94 HBV-related hepatocellular carcinoma (HCC) patients was sequenced by next-generation sequencing (NGS) and the percentages of nucleotide deletion in the preS region were analysed. Hierarchical clustering and heatmaps based on deletion percentages of preS revealed different deletion patterns between CHB and HCC patients...
October 12, 2017: Journal of General Virology
https://www.readbyqxmd.com/read/29022372/machine-learning-based-models-to-predict-modes-of-toxic-action-of-phenols-to-tetrahymena-pyriformis
#17
J A Castillo-Garit, G M Casañola-Martin, S J Barigye, H Pham-The, F Torrens, A Torreblanca
The phenols are structurally heterogeneous pollutants and they present a variety of modes of toxic action (MOA), including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles, and soft electrophiles. Because it is often difficult to determine correctly the mechanism of action of a compound, quantitative structure-activity relationship (QSAR) methods, which have proved their interest in toxicity prediction, can be used. In this work, several QSAR models for the prediction of MOA of 221 phenols to the ciliated protozoan Tetrahymena pyriformis, using Chemistry Development Kit descriptors, are reported...
September 2017: SAR and QSAR in Environmental Research
https://www.readbyqxmd.com/read/29021555/bypassing-the-kohn-sham-equations-with-machine-learning
#18
Felix Brockherde, Leslie Vogt, Li Li, Mark E Tuckerman, Kieron Burke, Klaus-Robert Müller
Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields. Machine learning holds the promise of learning the energy functional via examples, bypassing the need to solve the Kohn-Sham equations. This should yield substantial savings in computer time, allowing larger systems and/or longer time-scales to be tackled, but attempts to machine-learn this functional have been limited by the need to find its derivative...
October 11, 2017: Nature Communications
https://www.readbyqxmd.com/read/29021342/digging-deep-into-golgi-phenotypic-diversity-with-unsupervised-machine-learning
#19
Shaista Hussain, Xavier Le Guezennec, Wang Yi, Huang Dong, Joanne Chia, Ke Yiping, Lee Kee Khoon, Frédéric Bard
The synthesis of glycans and sorting of proteins are critical functions of the Golgi apparatus and depend on its highly complex and compartmentalized architecture. High-content image analysis coupled to RNAi screening offers opportunities to explore this organelle organisation and the gene network underlying it. To date, image-based Golgi screens were based on a single parameter or supervised analysis with pre-defined Golgi structural classes. Here, we report the use of multi-parametric data extracted from a single marker and a computational unsupervised analysis framework to explore Golgi phenotypic diversity more extensively...
October 11, 2017: Molecular Biology of the Cell
https://www.readbyqxmd.com/read/29021308/machine-learning-and-rare-variant-adjudication-in-type-1-long-qt-syndrome
#20
EDITORIAL
John R Giudicessi
No abstract text is available yet for this article.
October 2017: Circulation. Cardiovascular Genetics
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