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Real-time Detection of Aortic Valve in Echocardiography using Convolutional Neural Networks.

Current medical imaging
BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular h...

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signa...

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

Journal of neural engineering
OBJECTIVE: Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit h...

Selection of Semantic Relevant Healthcare Services Subsets.

Studies in health technology and informatics
We describe an approach to select semantically coherent specialty subsets based on the historical use of terminology by different service areas. Our approach uses rule-based and machine learning techniques to obtain a reduced set of 29 specialties.

DeepPhe: A Natural Language Processing System for Extracting Cancer Phenotypes from Clinical Records.

Cancer research
Precise phenotype information is needed to understand the effects of genetic and epigenetic changes on tumor behavior and responsiveness. Extraction and representation of cancer phenotypes is currently mostly performed manually, making it difficult t...

CD-KES: An Ontology Based Knowledge Education System for Patients with Chronic Diseases and Its Constructing Approach.

Studies in health technology and informatics
Patients' participation plays a crucial role in the management of chronic diseases. Educating patients about their diseases allows patients to self-regulate their daily health conditions more reasonably and effectively. This study focuses on an infor...

Development of a Service-Oriented Sharable Clinical Decision Support System Based on Ontology for Chronic Disease.

Studies in health technology and informatics
Clinical decision support systems (CDSSs) have been proved as an efficient way to improve health care quality. However, the inflexibility in integrating multiple clinical practice guidelines (multi-CPGs), the mass input workload of patient data, and ...

Architecture and Initial Development of a Digital Library Platform for Computable Knowledge Objects for Health.

Studies in health technology and informatics
Throughout the world, biomedical knowledge is routinely generated and shared through primary and secondary scientific publications. However, there is too much latency between publication of knowledge and its routine use in practice. To address this l...

Evaluation of Network-Based Minimally Invasive VR Surgery Simulator.

Studies in health technology and informatics
In this paper, we report a result of an experiment of a field trial of our network-based minimally invasive surgery simulator. In our previous paper, we proposed a network-based visuohaptic surgery training system for laparoscopic surgery. In additio...