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COVID-19

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Integrated epigenomic exposure signature discovery.

Epigenomics
The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Here we developed and implemented a machine learning algorithm, the exposure signature discove...

Artificial intelligence and telemedicine in epilepsy and EEG: A narrative review.

Seizure
The emergence of telemedicine and artificial intelligence (AI) has set the stage for a possible revolution in the future of medicine and neurology including the diagnosis and management of epilepsy. Telemedicine, with its proven efficacy during the C...

Special supplement issue on quality assurance and enrichment of biological and biomedical ontologies and terminologies.

BMC medical informatics and decision making
Ontologies and terminologies serve as the backbone of knowledge representation in biomedical domains, facilitating data integration, interoperability, and semantic understanding across diverse applications. However, the quality assurance and enrichme...

A deep convolutional neural network approach using medical image classification.

BMC medical informatics and decision making
The epidemic diseases such as COVID-19 are rapidly spreading all around the world. The diagnosis of epidemic at initial stage is of high importance to provide medical care to and recovery of infected people as well as protecting the uninfected popula...

Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online.

Nature communications
Given the profound societal impact of conspiracy theories, probing the psychological factors associated with their spread is paramount. Most research lacks large-scale behavioral outcomes, leaving factors related to actual online support for conspira...

Deep Learning-Based System Combining Chest X-Ray and Computerized Tomography Images for COVID-19 Diagnosis.

British journal of hospital medicine (London, England : 2005)
The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for accurate and efficient diagnostic methods. This study aims to improve COVID-19 detection by integrating chest X-ray (CXR) and computerized tomography (CT) images using dee...

Therapeutic Exercise Recognition Using a Single UWB Radar with AI-Driven Feature Fusion and ML Techniques in a Real Environment.

Sensors (Basel, Switzerland)
Physiotherapy plays a crucial role in the rehabilitation of damaged or defective organs due to injuries or illnesses, often requiring long-term supervision by a physiotherapist in clinical settings or at home. AI-based support systems have been devel...

COVID-19 severity detection using chest X-ray segmentation and deep learning.

Scientific reports
COVID-19 has resulted in a significant global impact on health, the economy, education, and daily life. The disease can range from mild to severe, with individuals over 65 or those with underlying medical conditions being more susceptible to severe i...

Long COVID diagnostic with differentiation from chronic lyme disease using machine learning and cytokine hubs.

Scientific reports
The absence of a long COVID (LC) or post-acute sequelae of COVID-19 (PASC) diagnostic has profound implications for research and potential therapeutics given the lack of specificity with symptom-based identification of LC and the overlap of symptoms ...