AIMC Topic: Deep Learning

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Evaluation of Effect of Curcumin on Psychological State of Patients with Pulmonary Hypertension by Magnetic Resonance Image under Deep Learning.

Contrast media & molecular imaging
This research aimed to evaluate the right ventricular segmentation ability of magnetic resonance imaging (MRI) images based on deep learning and evaluate the influence of curcumin (Cur) on the psychological state of patients with pulmonary hypertensi...

Product Inspection Methodology via Deep Learning: An Overview.

Sensors (Basel, Switzerland)
In this study, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. In addition, we explain the steps for buildin...

Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning.

Zeitschrift fur medizinische Physik
INTRODUCTION: Quantitative Susceptibility Mapping (QSM) is generally acquired with full brain coverage, even though many QSM brain-iron studies focus on the deep grey matter (DGM) region only. Reducing the spatial coverage to the DGM vicinity can sub...

Spatiotemporal modeling of land subsidence using a geographically weighted deep learning method based on PS-InSAR.

The Science of the total environment
The demand for water resources during urbanization forces the continuous exploitation of groundwater, resulting in dramatic piezometric drawdown and inducing regional land subsidence (LS). This has greatly threatened sustainable development in the lo...

Application of deep learning to identify COVID-19 infection in posteroanterior chest X-rays.

Clinical imaging
INTRODUCTION: The objective of this study was to assess seven configurations of six convolutional deep neural network architectures for classification of chest X-rays (CXRs) as COVID-19 positive or negative.

Detection of segmented uterine cancer images by Hotspot Detection method using deep learning models, Pigeon-Inspired Optimization, types-based dominant activation selection approaches.

Computers in biology and medicine
Uterine cancer consists of cells of a layer that forms the inside of the uterus. Sometimes, as a result of abnormal growth of normal cells, it can damage the surrounding tissues and cause the formation of cancerous cells. In the USA, according to the...

Spin-Orbit Torque-Induced Domain Nucleation for Neuromorphic Computing.

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic computing has become an increasingly popular approach for artificial intelligence because it can perform cognitive tasks more efficiently than conventional computers. However, it remains challenging to develop dedicated hardware for arti...

Deep Learning with Neuroimaging and Genomics in Alzheimer's Disease.

International journal of molecular sciences
A growing body of evidence currently proposes that deep learning approaches can serve as an essential cornerstone for the diagnosis and prediction of Alzheimer's disease (AD). In light of the latest advancements in neuroimaging and genomics, numerous...

Logistic matrix factorisation and generative adversarial neural network-based method for predicting drug-target interactions.

Molecular diversity
Identifying drug-target protein association pairs is a prerequisite and a crucial task in drug discovery and development. Numerous computational models, based on different assumptions and algorithms, have been proposed as an alternative to the labori...