AIMC Topic: Humans

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Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing.

Journal of translational medicine
BACKGROUND: The circadian system is responsible for regulating various physiological activities and behaviors and has been gaining recognition. The circadian rhythm is adjusted in a 24-h cycle and has transcriptional-translational feedback loops. Whe...

Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?

BMC medical research methodology
BACKGROUND: The health crisis resulting from the global COVID-19 pandemic highlighted more than ever the need for rapid, reliable and safe methods of diagnosis and monitoring of respiratory diseases. To study pulmonary involvement in detail, one of t...

Sleep staging classification based on a new parallel fusion method of multiple sources signals.

Physiological measurement
In the field of medical informatics, sleep staging is a challenging and time consuming task undertaken by sleep experts. The conventional method for sleep staging is to analyze Polysomnograms (PSGs) recorded in a sleep lab, but the sleep monitoring w...

Three-Dimensional Reconstruction of a CT Image under Deep Learning Algorithm to Evaluate the Application of Percutaneous Kyphoplasty in Osteoporotic Thoracolumbar Compression Fractures.

Contrast media & molecular imaging
In order to investigate the therapeutic evaluation of percutaneous kyphoplasty (PKP) for the treatment of osteoporotic thoracolumbar compression fractures by three-dimensional (3D) reconstruction of computed tomography (CT) based on the deep learning...

Artificial Intelligence-Based Cyber-Physical System for Severity Classification of Chikungunya Disease.

IEEE journal of translational engineering in health and medicine
BACKGROUND: Artificial intelligence techniques are widely used in solving medical problems. Recently, researchers have used various deep learning techniques for the severity classification of Chikungunya disease. But these techniques suffer from over...

Research on Feature Extraction and Chinese Translation Method of Internet-of-Things English Terminology.

Computational intelligence and neuroscience
Feature extraction and Chinese translation of Internet-of-Things English terms are the basis of many natural language processing. Its main purpose is to extract rich semantic information from unstructured texts to allow computers to further calculate...

An Entity Relationship Extraction Model Based on BERT-BLSTM-CRF for Food Safety Domain.

Computational intelligence and neuroscience
Dealing with food safety issues in time through online public opinion incidents can reduce the impact of incidents and protect human health effectively. Therefore, by the smart technology of extracting the entity relationship of public opinion events...

Stress Classification Using Brain Signals Based on LSTM Network.

Computational intelligence and neuroscience
The early diagnosis of stress symptoms is essential for preventing various mental disorder such as depression. Electroencephalography (EEG) signals are frequently employed in stress detection research and are both inexpensive and noninvasive modality...

English Text Recognition Deep Learning Framework to Automatically Identify Fake News.

Computational intelligence and neuroscience
Fake news spreading rapidly worldwide is considered one of the most severe problems of modern technology that needs to be addressed immediately. The remarkable increase in the use of social media as a critical source of information combined with the ...

ResNet-50 for 12-Lead Electrocardiogram Automated Diagnosis.

Computational intelligence and neuroscience
Nowadays, the implementation of Artificial Intelligence (AI) in medical diagnosis has attracted major attention within both the academic literature and industrial sector. AI would include deep learning (DL) models, where these models have been achiev...