AIMC Topic: Neural Networks, Computer

Clear Filters Showing 30081 to 30090 of 31376 articles

Human Locomotion Classification for Different Terrains Using Machine Learning Techniques.

Critical reviews in biomedical engineering
Gait analysis on healthy subjects was performed based on surface electromyographic and acceleration sensor signal, implemented through machine learning approaches. The surface EMG and 3-axes acceleration signals have been acquired for 5 different ter...

An Automatic Classification of the Early Osteonecrosis of Femoral Head with Deep Learning.

Current medical imaging
BACKGROUND: Osteonecrosis of Femoral Head (ONFH) is a common complication in orthopaedics, wherein femoral structures are usually damaged due to the impairment or interruption of femoral head blood supply.

Development of an Artificial Intelligence Model to Identify a Dental Implant from a Radiograph.

The International journal of oral & maxillofacial implants
PURPOSE: The objective of this study was to develop a deep convolutional neural network (CNN) that would identify the brand and model of a dental implant from a radiograph.

[Application of Convolutional Neural Network for Evaluating CT Dose Using Image Noise Classification: A Phantom Study].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: It is well known that there is a trade-off relationship between image noise and exposure dose in X-ray computed tomography (CT) examination. Therefore, CT dose level was evaluated by using the CT image noise property. Although noise power sp...

[Supplementing a Web-based Exposure Estimation System with Deep Learning for Automatic Classification of CT Images to Increase the Efficiency of Effective Dose Estimation].

Nihon Hoshasen Gijutsu Gakkai zasshi
PURPOSE: Web-based exposure estimation systems are advantageous for estimating exposure doses for computed tomography (CT) scans. However, such systems depend on the imaging conditions of the slices, and a considerable amount of time and effort is ne...

Multi-level 3D Densenets for False-positive Reduction in Lung Nodule Detection Based on Chest Computed Tomography.

Current medical imaging
OBJECTIVE: False-positive nodule reduction is a crucial part of a computer-aided detection (CADe) system, which assists radiologists in accurate lung nodule detection. In this research, a novel scheme using multi-level 3D DenseNet framework is propos...

Deep Learning: A Breakthrough in Medical Imaging.

Current medical imaging
Deep learning has attracted great attention in the medical imaging community as a promising solution for automated, fast and accurate medical image analysis, which is mandatory for quality healthcare. Convolutional neural networks and its variants ha...

Deep Learning for Acute Myeloid Leukemia Diagnosis.

Journal of medicine and life
By changing the lifestyle and increasing the cancer incidence, accurate diagnosis becomes a significant medical action. Today, DNA microarray is widely used in cancer diagnosis and screening since it is able to measure gene expression levels. Analyzi...

Automated Intensity Modulated Radiation Therapy Treatment Planning for Cervical Cancer Based on Convolution Neural Network.

Technology in cancer research & treatment
PURPOSE: To develop and evaluate an automatic intensity-modulated radiation therapy (IMRT) program for cervical cancer, including a Convolution Neural Network (CNN)-based prediction model and an automated optimization strategy.