Single Cell Image Correlation Analysis and Phenotypic Screening for Diabetic Cardiomyopathy
نویسندگان
چکیده
منابع مشابه
Deep image mining for diabetic retinopathy screening
Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually no expert knowledge about the target pathologies. However, deep learning algorithms, including the popular ConvNets, are black boxes: little is known about ...
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High-throughput image-based screening (also termed high-content screening) has become a popular method in systems biology, functional genomics and drug discovery. Data analysis of high-content screening can be divided into two steps: image quantification and phenotypic analysis. Previously we have developed two R packages, EBImage and imageHTS for image quantification. The current R package phe...
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AIMS Diabetic cardiomyopathy, characterized by left ventricular (LV) dysfunction and LV hypertrophy independent of myocardial ischaemia and hypertension, could contribute to the increased life-time risk of congestive heart failure seen in patients with diabetes. We assessed prospectively the prevalence, effectiveness of screening methods [brain natriuretic peptide (BNP) and C-reactive protein i...
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PURPOSE Diabetic patients with limited access to ophthalmologists have low screening rates for diabetic retinopathy. We evaluated a diabetic retinopathy screening program in a community health center using single images taken with a nonmydriatic retinal camera and primary care clinicians trained to read retinal images. METHODS This study was conducted from 2001 to 2004 in a multisite communit...
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ژورنال
عنوان ژورنال: Biophysical Journal
سال: 2015
ISSN: 0006-3495
DOI: 10.1016/j.bpj.2014.11.1762