Neural networks : the official journal of the International Neural Network Society
Nov 22, 2019
This paper proves an abstract theorem addressing in a unified manner two important problems in function approximation: avoiding curse of dimensionality and estimating the degree of approximation for out-of-sample extension in manifold learning. We co...
Knee arthroscopy is a minimally invasive surgery used in the treatment of intra-articular knee pathology which may cause unintended damage to femoral cartilage. An ultrasound (US)-guided autonomous robotic platform for knee arthroscopy can be envisio...
OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical ma...
Drug toxicity evaluation is an essential process of drug development as it is reportedly responsible for the attrition of approximately 30% of drug candidates. The rapid increase in the number and types of large toxicology data sets together with the...
OBJECTIVE: Epistasis identification is critical for determining susceptibility to human genetic diseases. The rapid development of technology has enabled scalability to make multifactor dimensionality reduction (MDR) measurements an effective calcula...
An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation...
BACKGROUND: The electrocardiogram (ECG) has been widely used in the diagnosis of heart disease such as arrhythmia due to its simplicity and non-invasive nature. Arrhythmia can be classified into many types, including life-threatening and non-life-thr...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 22, 2019
Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific arc...
PURPOSE: Human peripheral blood leukocytes' classification is important for diagnosing blood diseases. Many microscopic leukocyte image automatic detection methods are proposed. In recent years, convolutional neural networks (CNNs) are applied to mic...
PURPOSE: Deep learning is emerging in radiology due to the increased computational capabilities available to reading rooms. These computational developments have the ability to mimic the radiologist and may allow for more accurate tissue characteriza...
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