AIMC Topic: Neural Networks, Computer

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A novel artificial intelligence system for the assessment of bowel preparation (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The quality of bowel preparation is an important factor that can affect the effectiveness of a colonoscopy. Several tools, such as the Boston Bowel Preparation Scale (BBPS) and Ottawa Bowel Preparation Scale, have been developed ...

The neural and neurocomputational bases of recovery from post-stroke aphasia.

Nature reviews. Neurology
Language impairment, or aphasia, is a disabling symptom that affects at least one third of individuals after stroke. Some affected individuals will spontaneously recover partial language function. However, despite a growing number of investigations, ...

Building an Otoscopic screening prototype tool using deep learning.

Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
BACKGROUND: Otologic diseases are often difficult to diagnose accurately for primary care providers. Deep learning methods have been applied with great success in many areas of medicine, often outperforming well trained human observers. The aim of th...

A dual-stream deep convolutional network for reducing metal streak artifacts in CT images.

Physics in medicine and biology
Machine learning and deep learning are rapidly finding applications in the medical imaging field. In this paper, we address the long-standing problem of metal artifacts in computed tomography (CT) images by training a dual-stream deep convolutional n...

A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification.

International journal of computer assisted radiology and surgery
PURPOSE: Diagnosis of lung cancer requires radiologists to review every lung nodule in CT images. Such a process can be very time-consuming, and the accuracy is affected by many factors, such as experience of radiologists and available diagnosis time...

DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

Nature methods
We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves t...

Unsupervised neural network for evaluating the ability of the SF-36 instrument to differentiate individuals.

Eastern Mediterranean health journal = La revue de sante de la Mediterranee orientale = al-Majallah al-sihhiyah li-sharq al-mutawassit
BACKGROUND: Health-related quality of life (HRQoL) and well-being refer to the positive, subjective state that is contrary to illness. HRQoL instruments include some common questionnaires, which may often be understood differently depending on the le...

Attention-based recurrent neural network for influenza epidemic prediction.

BMC bioinformatics
BACKGROUND: Influenza is an infectious respiratory disease that can cause serious public health hazard. Due to its huge threat to the society, precise real-time forecasting of influenza outbreaks is of great value to our public.

A scalable multi-signal approach for the parallelization of self-organizing neural networks.

Neural networks : the official journal of the International Neural Network Society
Self-Organizing Neural Networks (SONNs) have a wide range of applications with massive computational requirements that often need to be satisfied with optimized parallel algorithms and implementations. In literature, SONN have been generally parallel...