Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study

Mojo Hand, a TALEN design tool for genome editing applications

(2013) Kevin L Neff et al.   BMC BIOINFORMATICS

Diabetic retinopathy screening and monitoring of early stage disease in general practice: Design and methods

(2012) Deborah A. Askew et al.   Contemporary Clinical Trials

Identifying Antigenicity-Associated Sites in Highly Pathogenic H5N1 Influenza Virus Hemagglutinin by Using Sparse Learning

(2012) Zhipeng Cai et al.   JOURNAL OF MOLECULAR BIOLOGY

A Microalbuminuria Threshold to Predict the Risk for the Development of Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients

(2012) Haibing Chen et al.   PLoS One

Multiple Regression Methods Show Great Potential for Rare Variant Association Tests

(2012) ChangJiang Xu et al.   PLoS One

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort

(2011) Hua Wang et al.   BIOINFORMATICS

Optimized application of penalized regression methods to diverse genomic data

(2011) Levi Waldron et al.   BIOINFORMATICS

Diagnosis and Classification of Diabetes Mellitus

(2011)   DIABETES CARE

Individual risk assessment and information technology to optimise screening frequency for diabetic retinopathy

(2011) T. Aspelund et al.   DIABETOLOGIA

Sparse Brain Network Recovery Under Compressed Sensing

(2011) Hyekyoung Lee et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Glycemic Thresholds for Diabetes-Specific Retinopathy: Implications for diagnostic criteria for diabetes

(2010) S. Colagiuri et al.   DIABETES CARE

SNP Selection in genome-wide and candidate gene studies via penalized logistic regression

(2010) Kristin L. Ayers et al.   GENETIC EPIDEMIOLOGY

Prevalence of Diabetic Retinopathy in the United States, 2005-2008

(2010) Xinzhi Zhang et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Diabetic retinopathy

(2010) Ning Cheung et al.   LANCET

Novel solutions for an old disease: Diagnosis of acute appendicitis with random forest, support vector machines, and artificial neural networks

(2010) Chung-Ho Hsieh et al.   SURGERY

Simple means to improve the interpretability of regression coefficients

(2010) Holger Schielzeth   Methods in Ecology and Evolution

Decompositional Rule Extraction from Support Vector Machines by Active Learning

(2009) D. Martens et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

A Sparse Learning Machine for High-Dimensional Data with Application to Microarray Gene Analysis

(2009) Qiang Cheng   IEEE-ACM Transactions on Computational Biology and Bioinformatics