AIMC Topic: Deep Learning

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Multi-Modal Deep Learning for Assessing Surgeon Technical Skill.

Sensors (Basel, Switzerland)
This paper introduces a new dataset of a surgical knot-tying task, and a multi-modal deep learning model that achieves comparable performance to expert human raters on this skill assessment task. Seventy-two surgical trainees and faculty were recruit...

Using Deep Learning for Task and Tremor Type Classification in People with Parkinson's Disease.

Sensors (Basel, Switzerland)
Hand tremor is one of the dominating symptoms of Parkinson's disease (PD), which significantly limits activities of daily living. Along with medications, wearable devices have been proposed to suppress tremor. However, suppressing tremor without inte...

A coarse-to-fine cascade deep learning neural network for segmenting cerebral aneurysms in time-of-flight magnetic resonance angiography.

Biomedical engineering online
BACKGROUND: Accurate segmentation of unruptured cerebral aneurysms (UCAs) is essential to treatment planning and rupture risk assessment. Currently, three-dimensional time-of-flight magnetic resonance angiography (3D TOF-MRA) has been the most common...

Point-of-care SARS-CoV-2 sensing using lens-free imaging and a deep learning-assisted quantitative agglutination assay.

Lab on a chip
The persistence of the global COVID-19 pandemic caused by the SARS-CoV-2 virus has continued to emphasize the need for point-of-care (POC) diagnostic tests for viral diagnosis. The most widely used tests, lateral flow assays used in rapid antigen tes...

A Novel Computer Vision Model for Medicinal Plant Identification Using Log-Gabor Filters and Deep Learning Algorithms.

Computational intelligence and neuroscience
Computer vision is the science that enables computers and machines to see and perceive image content on a semantic level. It combines concepts, techniques, and ideas from various fields such as digital image processing, pattern matching, artificial i...

Forest Environmental Carrying Capacity Based on Deep Learning.

Computational intelligence and neuroscience
In this paper, we proposed an assessment system of forest environmental carrying capacity from many aspects and comprehensively evaluated and predicted the forest environmental carrying capacity of 40 cities in the Yangtze River Delta of China by usi...

Rolling Bearing Fault Detection System and Experiment Based on Deep Learning.

Computational intelligence and neuroscience
The current situation of frequent small-scale accidents shows that the existing methods have not completely solved the problem of bearing failures, and new research methods need to be used to complete the study of bearing failures. To prevent the fai...

A Deep Learning Model for Idiopathic Osteosclerosis Detection on Panoramic Radiographs.

Medical principles and practice : international journal of the Kuwait University, Health Science Centre
OBJECTIVE: The purpose of the study was to create an artificial intelligence (AI) system for detecting idiopathic osteosclerosis (IO) on panoramic radiographs for automatic, routine, and simple evaluations.

Deep learning reconstruction in pediatric brain MRI: comparison of image quality with conventional T2-weighted MRI.

Neuroradiology
INTRODUCTION: Deep learning-based MRI reconstruction has recently been introduced to improve image quality. This study aimed to evaluate the performance of deep learning reconstruction in pediatric brain MRI.

Computer aided detection of tuberculosis using two classifiers.

Biomedizinische Technik. Biomedical engineering
Tuberculosis caused by Mycobacterium tuberculosis have been a major challenge for medical and healthcare sectors in many underdeveloped countries with limited diagnosis tools. Tuberculosis can be detected from microscopic slides and chest X-ray but a...