OBJECTIVE: To develop and evaluate a multi-path synergic fusion (MSF) deep neural network model for breast mass classification using digital breast tomosynthesis (DBT).
IEEE journal of biomedical and health informatics
Dec 4, 2020
Deep learning methods for diabetic retinopathy (DR) diagnosis are usually criticized as being lack of interpretability in the diagnostic result, thus limiting their application in clinic. Simultaneous prediction of DR related features during the DR s...
IEEE journal of biomedical and health informatics
Dec 4, 2020
The gold standard clinical tool for evaluating visual dysfunction in cases of glaucoma and other disorders of vision remains the visual field or threshold perimetry exam. Administration of this exam has evolved over the years into a sophisticated, st...
IEEE journal of biomedical and health informatics
Dec 4, 2020
Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities in diagnosis of these diseases ...
IEEE journal of biomedical and health informatics
Dec 4, 2020
Cataracts are the leading cause of visual impairment worldwide. Examination of the retina through cataracts using a fundus camera is challenging and error-prone due to degraded image quality. We sought to develop an algorithm to dehaze such images to...
IEEE journal of biomedical and health informatics
Dec 4, 2020
Sleep stage scoring is the first step towards quantitative analysis of sleep using polysomnography (PSG) recordings. However, although PSG is a gold standard method for assessing sleep, it is obtrusive and difficult to apply for long-term sleep monit...
BACKGROUND: Accurate prediction of thyroidectomy complications is necessary to inform treatment decisions. Ensemble machine learning provides one approach to improve prediction.
Extreme gradient boosting methods outperform conventional machine-learning models. Here, we have developed the LEukemia Artificial intelligence Program (LEAP) with the extreme gradient boosting decision tree method for the optimal treatment recommend...
BACKGROUND: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT meas...
Visual field assessment is recognized as the important criterion of glaucomatous damage judgement; however, it can show large test-retest variability. We developed a deep learning (DL) algorithm that quantitatively predicts mean deviation (MD) of sta...
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