keyword
MENU ▼
Read by QxMD icon Read
search

Lasso

keyword
https://www.readbyqxmd.com/read/28208229/comparing-the-performance-of-propensity-score-methods-in-healthcare-database-studies-with-rare-outcomes
#1
Jessica M Franklin, Wesley Eddings, Peter C Austin, Elizabeth A Stuart, Sebastian Schneeweiss
Nonrandomized studies of treatments from electronic healthcare databases are critical for producing the evidence necessary to making informed treatment decisions, but often rely on comparing rates of events observed in a small number of patients. In addition, studies constructed from electronic healthcare databases, for example, administrative claims data, often adjust for many, possibly hundreds, of potential confounders. Despite the importance of maximizing efficiency when there are many confounders and few observed outcome events, there has been relatively little research on the relative performance of different propensity score methods in this context...
February 16, 2017: Statistics in Medicine
https://www.readbyqxmd.com/read/28199892/a-prognostic-index-pi-as-a-moderator-of-outcomes-in-the-treatment-of-depression-a-proof-of-concept-combining-multiple-variables-to-inform-risk-stratified-stepped-care-models
#2
Lorenzo Lorenzo-Luaces, Robert J DeRubeis, Annemieke van Straten, Bea Tiemens
BACKGROUND: Prognostic indices (PIs) combining variables to predict future depression risk may help guide the selection of treatments that differ in intensity. We develop a PI and show its promise in guiding treatment decisions between treatment as usual (TAU), treatment starting with a low-intensity treatment (brief therapy (BT)), or treatment starting with a high-intensity treatment intervention (cognitive-behavioral therapy (CBT)). METHODS: We utilized data from depressed patients (N=622) who participated in a randomized comparison of TAU, BT, and CBT in which no statistically significant differences in the primary outcomes emerged between the three treatments...
February 7, 2017: Journal of Affective Disorders
https://www.readbyqxmd.com/read/28199352/nearest-shrunken-centroids-via-alternative-genewise-shrinkages
#3
Byeong Yeob Choi, Eric Bair, Jae Won Lee
Nearest shrunken centroids (NSC) is a popular classification method for microarray data. NSC calculates centroids for each class and "shrinks" the centroids toward 0 using soft thresholding. Future observations are then assigned to the class with the minimum distance between the observation and the (shrunken) centroid. Under certain conditions the soft shrinkage used by NSC is equivalent to a LASSO penalty. However, this penalty can produce biased estimates when the true coefficients are large. In addition, NSC ignores the fact that multiple measures of the same gene are likely to be related to one another...
2017: PloS One
https://www.readbyqxmd.com/read/28195687/the-adjustable-slipknot-technique-for-implanting-neochordae-in-the-repair-of-mitral-valve-prolapse
#4
Mitsuhiro Yano, Masakazu Matsuyama, Masanori Nishimura, Katsuya Kawagoe
The adjustable slipknot technique is a novel procedure for implanting neochordae. The neochorda acts like a lasso. The procedure facilitates accurate assessment of the length of the neochordae. We performed repairs for 30 of 31 (97.7%) patients using this technique. Less than mild residual regurgitation was observed in all patients at hospital discharge.
December 6, 2016: Multimedia Manual of Cardiothoracic Surgery: MMCTS
https://www.readbyqxmd.com/read/28192605/stagewise-generalized-estimating-equations-with-grouped-variables
#5
Gregory Vaughan, Robert Aseltine, Kun Chen, Jun Yan
Forward stagewise estimation is a revived slow-brewing approach for model building that is particularly attractive in dealing with complex data structures for both its computational efficiency and its intrinsic connections with penalized estimation. Under the framework of generalized estimating equations, we study general stagewise estimation approaches that can handle clustered data and non-Gaussian/non-linear models in the presence of prior variable grouping structure. As the grouping structure is often not ideal in that even the important groups may contain irrelevant variables, the key is to simultaneously conduct group selection and within-group variable selection, that is, bi-level selection...
February 13, 2017: Biometrics
https://www.readbyqxmd.com/read/28187708/incorporating-prior-biological-knowledge-for-network-based-differential-gene-expression-analysis-using-differentially-weighted-graphical-lasso
#6
Yiming Zuo, Yi Cui, Guoqiang Yu, Ruijiang Li, Habtom W Ressom
BACKGROUND: Conventional differential gene expression analysis by methods such as student's t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them. Network-based approaches provide a natural way to study these interactions and to investigate the rewiring interactions in disease versus control groups. In this paper, we apply weighted graphical LASSO (wgLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i...
February 10, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28186904/a-combined-pls-and-negative-binomial-regression-model-for-inferring-association-networks-from-next-generation-sequencing-count-data
#7
Maiju Pesonen, Jaakko Nevalainen, Steven Potter, Somnath Datta, Susmita Datta
A major challenge of genomics data is to detect interactions displaying functional associations from large-scale observations. In this study, a new cPLS-algorithm combining partial least squares approach with negative binomial regression is suggested to reconstruct a genomic association network for high-dimensional next-generation sequencing count data. The suggested approach is applicable to the raw counts data, without requiring any further pre-processing steps. In the settings investigated, the cPLS-algorithm outperformed the two widely used comparative methods, graphical lasso and weighted correlation network analysis...
February 7, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28185992/lasso-plate-an-original-implant-for-fixation-of-type-i-and-ii-regan-morrey-coronoid-fractures
#8
Pengfei Wang, Yan Zhuang, Zhong Li, Wei Wei, Yahui Fu, Xing Wei, Kun Zhang
INTRODUCTION: Coronoid fractures are notoriously difficult to manage particularly when there is a small fragment. We report a retrospective analysis of our experience with consecutive type I and II Regan-Morrey coronoid fractures using a lasso plate. HYPOTHESIS: Type I and II Regan-Morrey coronoid fractures can be effectively managed using a lasso plate. METHODS: From October, 2011 and December, 2013, 25 patients(21 males and 4 females, mean age 40...
February 6, 2017: Orthopaedics & Traumatology, Surgery & Research: OTSR
https://www.readbyqxmd.com/read/28182849/controlling-the-false-discoveries-in-lasso
#9
Hanwen Huang
The LASSO method estimates coefficients by minimizing the residual sum of squares plus a penalty term. The regularization parameter λ in LASSO controls the trade-off between data fitting and sparsity. We derive relationship between λ and the false discovery proportion (FDP) of LASSO estimator and show how to select λ so as to achieve a desired FDP. Our estimation is based on the asymptotic distribution of LASSO estimator in the limit of both sample size and dimension going to infinity with fixed ratio. We use a factor analysis model to describe the dependence structure of the design matrix...
February 9, 2017: Biometrics
https://www.readbyqxmd.com/read/28180924/ct-based-radiomics-signature-a-potential-biomarker-for-preoperative-prediction-of-early-recurrence-in-hepatocellular-carcinoma
#10
Ying Zhou, Lan He, Yanqi Huang, Shuting Chen, Penqi Wu, Weitao Ye, Zaiyi Liu, Changhong Liang
PURPOSE: To develop a CT-based radiomics signature and assess its ability for preoperatively predicting the early recurrence (≤1 year) of hepatocellular carcinoma (HCC). METHODS: A total of 215 HCC patients who underwent partial hepatectomy were enrolled in this retrospective study, and all the patients were followed up at least within 1 year. Radiomics features were extracted from arterial- and portal venous-phase CT images, and a radiomics signature was built by the least absolute shrinkage and selection operator (LASSO) logistic regression model...
February 8, 2017: Abdominal Radiology
https://www.readbyqxmd.com/read/28179471/metabolomic-biomarkers-as-strong-correlates-of-parkinson-disease-progression
#11
Peter A LeWitt, Jia Li, Mei Lu, Lining Guo, Peggy Auinger
OBJECTIVE: To determine whether a Parkinson disease (PD)-specific biochemical signature might be found in the total body metabolic milieu or in the CSF compartment, especially since this disorder has systemic manifestations beyond the progressive loss of dopaminergic nigrostriatal neurons. METHODS: Our goal was to discover biomarkers of PD progression. Using ultra-high-performance liquid chromatography linked to gas chromatography and tandem mass spectrometry, we measured concentrations of small-molecule (≤1...
February 8, 2017: Neurology
https://www.readbyqxmd.com/read/28176850/application-of-machine-learning-models-to-predict-tacrolimus-stable-dose-in-renal-transplant-recipients
#12
Jie Tang, Rong Liu, Yue-Li Zhang, Mou-Ze Liu, Yong-Fang Hu, Ming-Jie Shao, Li-Jun Zhu, Hua-Wen Xin, Gui-Wen Feng, Wen-Jun Shang, Xiang-Guang Meng, Li-Rong Zhang, Ying-Zi Ming, Wei Zhang
Tacrolimus has a narrow therapeutic window and considerable variability in clinical use. Our goal was to compare the performance of multiple linear regression (MLR) and eight machine learning techniques in pharmacogenetic algorithm-based prediction of tacrolimus stable dose (TSD) in a large Chinese cohort. A total of 1,045 renal transplant patients were recruited, 80% of which were randomly selected as the "derivation cohort" to develop dose-prediction algorithm, while the remaining 20% constituted the "validation cohort" to test the final selected algorithm...
February 8, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28167911/quantitative-eeg-qeeg-measures-differentiate-parkinson-s-disease-pd-patients-from-healthy-controls-hc
#13
Menorca Chaturvedi, Florian Hatz, Ute Gschwandtner, Jan G Bogaarts, Antonia Meyer, Peter Fuhr, Volker Roth
Objectives: To find out which Quantitative EEG (QEEG) parameters could best distinguish patients with Parkinson's disease (PD) with and without Mild Cognitive Impairment from healthy individuals and to find an optimal method for feature selection. Background: Certain QEEG parameters have been seen to be associated with dementia in Parkinson's and Alzheimer's disease. Studies have also shown some parameters to be dependent on the stage of the disease. We wanted to investigate the differences in high-resolution QEEG measures between groups of PD patients and healthy individuals, and come up with a small subset of features that could accurately distinguish between the two groups...
2017: Frontiers in Aging Neuroscience
https://www.readbyqxmd.com/read/28161476/markers-of-neuroinflammation-associated-with-alzheimer-s-disease-pathology-in-older-adults
#14
Julius Popp, Aikaterini Oikonomidi, Domilė Tautvydaitė, Loïc Dayon, Michael Bacher, Eugenia Migliavacca, Hugues Henry, Richard Kirkland, India Severin, Jérôme Wojcik, Gene L Bowman
BACKGROUND: In vitro and animal studies have linked neuroinflammation to Alzheimer's disease (AD) pathology. Studies on markers of inflammation in subjects with mild cognitive impairment or AD dementia provided inconsistent results. We hypothesized that distinct blood and cerebrospinal fluid (CSF) inflammatory markers are associated with biomarkers of amyloid and tau pathology in older adults without cognitive impairment or with beginning cognitive decline. OBJECTIVE: To identify blood-based and CSF neuroinflammation marker signatures associated with AD pathology (i...
February 1, 2017: Brain, Behavior, and Immunity
https://www.readbyqxmd.com/read/28160691/subject-specific-abnormal-region-detection-in-traumatic-brain-injury-using-sparse-model-selection-on-high-dimensional-diffusion-data
#15
Matineh Shaker, Deniz Erdogmus, Jennifer Dy, Sylvain Bouix
We present a method to estimate a multivariate Gaussian distribution of diffusion tensor features in a set of brain regions based on a small sample of healthy individuals, and use this distribution to identify imaging abnormalities in subjects with mild traumatic brain injury. The multivariate model receives apriori knowledge in the form of a neighborhood graph imposed on the precision matrix, which models brain region interactions, and an additional L1 sparsity constraint. The model is then estimated using the graphical LASSO algorithm and the Mahalanobis distance of healthy and TBI subjects to the distribution mean is used to evaluate the discriminatory power of the model...
January 24, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28160492/a-prognostic-4-gene-expression-signature-for-squamous-cell-lung-carcinoma
#16
Jun Li, Jing Wang, Yanbin Chen, Lijie Yang, Sheng Chen
Squamous cell lung carcinoma (SQCLC), a common and fatal subtype of lung cancer, caused lots of mortalities and showed different outcomes in prognosis. This study was to screen key genes and to figure a prognostic signature to cluster the patients with SQCLC. RNA-Seq data from 550 patients with SQCLC were downloaded from The Cancer Genome Atlas (TCGA). Genetically changed genes were identified and analyzed in univariate survival analysis. Genes significantly influencing prognosis were selected with frequency higher than 100 in lasso regression...
February 4, 2017: Journal of Cellular Physiology
https://www.readbyqxmd.com/read/28157321/breast-cancer-targeting-peptide-binds-keratin-1-a-new-molecular-marker-for-targeted-drug-delivery-to-breast-cancer
#17
Rania Soudy, Hashem Rajab Etayash, Kamran Bahadorani, Afsaneh Lavasanifar, Kamaljit Kaur
The biomarkers or receptors expressed on cancer cells and the targeting ligands with high binding affinity for biomarkers play a key role in early detection and treatment of breast cancer. The breast cancer targeting peptide p160 (12-mer) and its enzymatically stable analogue 18-4 (10-mer) showed marked potential for breast cancer drug delivery using cell studies and animal models. Herein, we used affinity purification, liquid chromatography-tandem mass spectrometry, and proteomics to identify keratin 1 (KRT1) as the target receptor highly expressed on breast cancer cells for p160 peptide(s)...
February 3, 2017: Molecular Pharmaceutics
https://www.readbyqxmd.com/read/28154510/multiple-group-testing-procedures-for-analysis-of-high-dimensional-genomic-data
#18
Hyoseok Ko, Kipoong Kim, Hokeun Sun
In genetic association studies with high-dimensional genomic data, multiple group testing procedures are often required in order to identify disease/trait-related genes or genetic regions, where multiple genetic sites or variants are located within the same gene or genetic region. However, statistical testing procedures based on an individual test suffer from multiple testing issues such as the control of family-wise error rate and dependent tests. Moreover, detecting only a few of genes associated with a phenotype outcome among tens of thousands of genes is of main interest in genetic association studies...
December 2016: Genomics & Informatics
https://www.readbyqxmd.com/read/28154505/prediction-of-quantitative-traits-using-common-genetic-variants-application-to-body-mass-index
#19
Sunghwan Bae, Sungkyoung Choi, Sung Min Kim, Taesung Park
With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog...
December 2016: Genomics & Informatics
https://www.readbyqxmd.com/read/28154504/risk-prediction-using-genome-wide-association-studies-on-type-2-diabetes
#20
Sungkyoung Choi, Sunghwan Bae, Taesung Park
The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the "large p and small n" problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN)...
December 2016: Genomics & Informatics
keyword
keyword
78480
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"