AIMC Topic: Deep Learning

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A deep learning risk prediction model for overall survival in patients with gastric cancer: A multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Risk prediction of overall survival (OS) is crucial for gastric cancer (GC) patients to assess the treatment programs and may guide personalized medicine. A novel deep learning (DL) model was proposed to predict the risk for O...

Convolutional neural network for detection and classification of seizures in clinical data.

Medical & biological engineering & computing
Epileptic seizure detection and classification in clinical electroencephalogram data still is a challenge, and only low sensitivity with a high rate of false positives has been achieved with commercially available seizure detection tools, which usual...

Toward automatic C-arm positioning for standard projections in orthopedic surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Guidance and quality control in orthopedic surgery increasingly rely on intra-operative fluoroscopy using a mobile C-arm. The accurate acquisition of standardized and anatomy-specific projections is essential in this process. The correspondi...

High-quality photoacoustic image reconstruction based on deep convolutional neural network: towards intra-operative photoacoustic imaging.

Biomedical physics & engineering express
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...

The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm.

International journal of environmental research and public health
In the context of rapid urbanization, the spread of cities in the Yangtze River Economic Belt is intensifying, which has an impact on the green and sustainable development of these cities. It is necessary to establish an accurate urban sprawl measure...

BIRADS features-oriented semi-supervised deep learning for breast ultrasound computer-aided diagnosis.

Physics in medicine and biology
We propose a novel BIRADS-SSDL network that integrates clinically-approved breast lesion characteristics (BIRADS features) into task-oriented semi-supervised deep learning (SSDL) for accurate diagnosis of ultrasound (US) images with a small training ...

R-ELMNet: Regularized extreme learning machine network.

Neural networks : the official journal of the International Neural Network Society
Principal component analysis network (PCANet), as an unsupervised shallow network, demonstrates noticeable effectiveness on datasets of various volumes. It carries a two-layer convolution with PCA as filter learning method, followed by a block-wise h...

A gentle introduction to deep learning for graphs.

Neural networks : the official journal of the International Neural Network Society
The adaptive processing of graph data is a long-standing research topic that has been lately consolidated as a theme of major interest in the deep learning community. The snap increase in the amount and breadth of related research has come at the pri...

Artificial Intelligence and Echocardiography: A Primer for Cardiac Sonographers.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Artificial intelligence (AI) is emerging as a key component in diagnostic medical imaging, including echocardiography. AI with deep learning has already been used with automated view labeling, measurements, and interpretation. As the development and ...

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

American journal of medical genetics. Part A
Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differe...