AIMC Topic: Deep Learning

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Analyzing variation of water inflow to inland lakes under climate change: Integrating deep learning and time series data mining.

Environmental research
The alarming depletion of global inland lakes in recent decades makes it essential to predict water inflow from rivers to lakes (WIRL) trend and unveil the dominant influencing driver, particularly in the context of climate change. The raw time serie...

Artificial intelligence in hepatocellular carcinoma diagnosis: a comprehensive review of current literature.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) diagnosis mainly relies on its pathognomonic radiological profile, obviating the need for biopsy. The project of incorporating artificial intelligence (AI) techniques in HCC aims to improve the perfo...

A Label-Efficient Framework for Automated Sinonasal CT Segmentation in Image-Guided Surgery.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Segmentation, the partitioning of patient imaging into multiple, labeled segments, has several potential clinical benefits but when performed manually is tedious and resource intensive. Automated deep learning (DL)-based segmentation metho...

Integrative deep learning with prior assisted feature selection.

Statistics in medicine
Integrative analysis has emerged as a prominent tool in biomedical research, offering a solution to the "small and large " challenge. Leveraging the powerful capabilities of deep learning in extracting complex relationship between genes and disease...

Deep learning in sex estimation from photographed human mandible using the Human Osteological Research Collection.

Legal medicine (Tokyo, Japan)
Sex estimation is a necessary part of forensic and osteological analyses of skeletal human remains in the construction of a biological profile. Several skeletal traits are sexually dimorphic and used for skeletal sex estimation. The human mandible an...

Unsupervised Segmentation of 3D Microvascular Photoacoustic Images Using Deep Generative Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mesoscopic photoacoustic imaging (PAI) enables label-free visualization of vascular networks in tissues with high contrast and resolution. Segmenting these networks from 3D PAI data and interpreting their physiological and pathological significance i...

Image-based facial emotion recognition using convolutional neural network on emognition dataset.

Scientific reports
Detecting emotions from facial images is difficult because facial expressions can vary significantly. Previous research on using deep learning models to classify emotions from facial images has been carried out on various datasets that contain a limi...

Deep Learning-Enabled Automated Quality Control for Liver MR Elastography: Initial Results.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.

Deep learning-based detection of lumbar spinal canal stenosis using convolutional neural networks.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Lumbar spinal canal stenosis (LSCS) is the most common spinal degenerative disorder in elderly people and usually first seen by primary care physicians or orthopedic surgeons who are not spine surgery specialists. Magnetic resonan...

Magnitude and angle dynamics in training single ReLU neurons.

Neural networks : the official journal of the International Neural Network Society
Understanding the training dynamics of deep ReLU networks is a significant area of interest in deep learning. However, there remains a lack of complete elucidation regarding the weight vector dynamics, even for single ReLU neurons. To bridge this gap...