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Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

Journal of Zhejiang University. Science. B
Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice,...

An empirical study of parallel solutions for GLCM calculation of diffraction images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Feature calculation of large amount of images is time consuming. The GPU based CUDA framework offers an affordable solution for calculating image features in parallel. The research focused on an empirical study of different implementations of a gener...

Alignment-Free Methods for the Detection and Specificity Prediction of Adenylation Domains.

Methods in molecular biology (Clifton, N.J.)
Identifying adenylation domains (A-domains) and their substrate specificity can aid the detection of nonribosomal peptide synthetases (NRPS) at genome/proteome level and allow inferring the structure of oligopeptides with relevant biological activiti...

Ontology-based Semantic Support to Improve Accessibility of Graphics.

Studies in health technology and informatics
We aim to ease the process of authoring accessible graphics as well as taking a first step towards the long-term goal of allowing blind persons to access graphics autonomously. We are developing and experimenting with a hierarchical set of knowledge ...

Augmented Reality: Real-Time Information Concerning Medication Consumed by a Patient.

Studies in health technology and informatics
This paper describes a mobile prototype capable of recognizing characters from a photograph of a medication package. The prototype was built to work on the iOS platform and was developed using Objective-C and C programming languages. The prototype, c...

Efficient training of convolutional deep belief networks in the frequency domain for application to high-resolution 2D and 3D images.

Neural computation
Deep learning has traditionally been computationally expensive, and advances in training methods have been the prerequisite for improving its efficiency in order to expand its application to a variety of image classification problems. In this letter,...