AIMC Topic:
Image Interpretation, Computer-Assisted
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Toward a Better Estimation of Functional Brain Network for Mild Cognitive Impairment Identification: A Transfer Learning View.
IEEE journal of biomedical and health informatics
Aug 9, 2019
Mild cognitive impairment (MCI) is an intermediate stage of brain cognitive decline, associated with increasing risk of developing Alzheimer's disease (AD). It is believed that early treatment of MCI could slow down the progression of AD, and functio...
Machine learning for tissue diagnostics in oncology: brave new world.
British journal of cancer
Aug 9, 2019
Machine learning is an exciting technology with broad application in big data analysis, as well as increasingly in specialised healthcare. As a diagnostic tool in tissue workup and pathology, it has the potential for personalised and stratified appro...
Machine learning-based prediction of breast cancer growth rate in vivo.
British journal of cancer
Aug 9, 2019
BACKGROUND: Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the r...
Deep neural networks are superior to dermatologists in melanoma image classification.
European journal of cancer (Oxford, England : 1990)
Aug 8, 2019
BACKGROUND: Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable in classifying images of benign nevi and melanoma with dermatologist-level preci...
Relative Afferent Pupillary Defect Screening Through Transfer Learning.
IEEE journal of biomedical and health informatics
Aug 7, 2019
Abnormalities in pupillary light reflex can indicate optic nerve disorders that may lead to permanent visual loss if not diagnosed in an early stage. In this study, we focus on relative afferent pupillary defect (RAPD), which is based on the differen...
Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67.
IEEE transactions on medical imaging
Aug 7, 2019
Immunohistochemistry (IHC) of ER, PR, and Ki-67 are routinely used assays in breast cancer diagnostics. Determination of the proportion of stained cells (labeling index) should be restricted on malignant epithelial cells, carefully avoiding tumor inf...
Deep learning how to fit an intravoxel incoherent motion model to diffusion-weighted MRI.
Magnetic resonance in medicine
Aug 7, 2019
PURPOSE: This prospective clinical study assesses the feasibility of training a deep neural network (DNN) for intravoxel incoherent motion (IVIM) model fitting to diffusion-weighted MRI (DW-MRI) data and evaluates its performance.
Algorithms
Prospective Studies
Computer Simulation
Reproducibility of Results
Humans
Bayes Theorem
Least-Squares Analysis
Motion
Image Interpretation, Computer-Assisted
Pancreas
Spleen
Diffusion Magnetic Resonance Imaging
Deep Learning
Image Processing, Computer-Assisted
Kidney
Liver
Adult
Male
Middle Aged
Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey.
Artificial intelligence in medicine
Aug 7, 2019
Diabetic retinopathy (DR) results in vision loss if not treated early. A computer-aided diagnosis (CAD) system based on retinal fundus images is an efficient and effective method for early DR diagnosis and assisting experts. A computer-aided diagnosi...
A Deep Learning Model to Triage Screening Mammograms: A Simulation Study.
Radiology
Aug 6, 2019
Background Recent deep learning (DL) approaches have shown promise in improving sensitivity but have not addressed limitations in radiologist specificity or efficiency. Purpose To develop a DL model to triage a portion of mammograms as cancer free, i...
Automatic cataract grading methods based on deep learning.
Computer methods and programs in biomedicine
Aug 5, 2019
BACKGROUND AND OBJECTIVE: The shortage of ophthalmologists in rural areas in China causes a lot of cataract patients not getting timely diagnosis and effective treatment. We develop an algorithm and platform to automatically diagnose and grade catara...
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