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Cardiac Rhythm Device Identification Using Neural Networks.

JACC. Clinical electrophysiology
OBJECTIVES: This paper reports the development, validation, and public availability of a new neural network-based system which attempts to identify the manufacturer and even the model group of a pacemaker or defibrillator from a chest radiograph.

Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images.

Medical physics
PURPOSE: Automatic segmentation of organs-at-risk (OARs) is a key step in radiation treatment planning to reduce human efforts and bias. Deep convolutional neural networks (DCNN) have shown great success in many medical image segmentation application...

Changes in the expression of four ABC transporter genes in response to imidacloprid in Bemisia tabaci Q (Hemiptera: Aleyrodidae).

Pesticide biochemistry and physiology
Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), a globally invasive species complex that causes serious damage to field crops, has developed resistance to imidacloprid and many other pesticides. Insect detoxify to pesticides may partially depend...

Chest Radiographs in Congestive Heart Failure: Visualizing Neural Network Learning.

Radiology
Purpose To examine Generative Visual Rationales (GVRs) as a tool for visualizing neural network learning of chest radiograph features in congestive heart failure (CHF). Materials and Methods A total of 103 489 frontal chest radiographs in 46 712 pati...

3-D Neural denoising for low-dose Coronary CT Angiography (CCTA).

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
CCTA has become an important tool for coronary arteries assessment in low and medium risk patients. However, it exposes the patient to significant radiation doses, resulting from high image quality requirements and acquisitions at multiple cardiac ph...

An Uncontrolled Manifold Analysis of Arm Joint Variability in Virtual Planar Position and Orientation Telemanipulation.

IEEE transactions on bio-medical engineering
OBJECTIVE: In teleoperated robot-assisted tasks, the user interacts with manipulators to finely control remote tools. Manipulation of robotic devices, characterized by specific kinematic and dynamic proprieties, is a complex task for the human sensor...

Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT.

IEEE transactions on medical imaging
Epicardial adipose tissue (EAT) is a visceral fat deposit related to coronary artery disease. Fully automated quantification of EAT volume in clinical routine could be a timesaving and reliable tool for cardiovascular risk assessment. We propose a ne...

Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network.

IEEE transactions on medical imaging
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in clinical applications. Iterative reconstruction algorithms are one of the most promising way to compensate for the increased noise due to reduction of photon flu...

Performance comparison between wrist and chest actigraphy in combination with heart rate variability for sleep classification.

Computers in biology and medicine
The concurrent usage of actigraphy and heart rate variability (HRV) for sleep efficiency quantification is still matter of investigation. This study compared chest (CACT) and wrist (WACT) actigraphy (actigraphs positioned on chest and wrist, respecti...

Osteopathic manual therapy in heart failure patients: A randomized clinical trial.

Journal of bodywork and movement therapies
BACKGROUND: Heart Failure (HF) patients usually present with increased arterial resistance and reduced blood pressure (BP) leading to an impaired functional capacity. Osteopathic Manual Therapy (OMT) focused on myofascial release techniques (MRT) and...