AIMC Topic: Databases, Factual

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Applying Deep Neural Networks over Homomorphic Encrypted Medical Data.

Computational and mathematical methods in medicine
In recent years, powered by state-of-the-art achievements in a broad range of areas, machine learning has received considerable attention from the healthcare sector. Despite their ability to provide solutions within personalized medicine, strict regu...

Dense gate network for biomedical image segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning has recently shown its outstanding performance in biomedical image semantic segmentation. Most biomedical semantic segmentation frameworks comprise the encoder-decoder architecture directly fusing features of the encoder and th...

Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Pharmacological research
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data ...

Dynamic Hand Gesture Recognition Based on a Leap Motion Controller and Two-Layer Bidirectional Recurrent Neural Network.

Sensors (Basel, Switzerland)
Dynamic hand gesture recognition is one of the most significant tools for human-computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network for the ...

Deep Learning to Unveil Correlations between Urban Landscape and Population Health.

Sensors (Basel, Switzerland)
The global healthcare landscape is continuously changing throughout the world as technology advances, leading to a gradual change in lifestyle. Several diseases such as asthma and cardiovascular conditions are becoming more diffuse, due to a rise in ...

A Novel Deep Neural Network for Robust Detection of Seizures Using EEG Signals.

Computational and mathematical methods in medicine
The detection of recorded epileptic seizure activity in electroencephalogram (EEG) segments is crucial for the classification of seizures. Manual recognition is a time-consuming and laborious process that places a heavy burden on neurologists, and he...

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks.

Physical and engineering sciences in medicine
In this study, a dataset of X-ray images from patients with common bacterial pneumonia, confirmed Covid-19 disease, and normal incidents, was utilized for the automatic detection of the Coronavirus disease. The aim of the study is to evaluate the per...

A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning algorithm that could predict individual cell immunophenotype based on hematoxylin and eosin (H&E) staining would save money, time, and reduce tissue co...

A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo, Egypt.

International journal of injury control and safety promotion
The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequentl...

Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs), a popular type of deep neural network, have been actively applied to image recognition, object detection, object localization, semantic segmentation, and object instance segmentation. Accordingly, the applicabili...