Infectious Disease

Prediction of nucleosome dynamic interval based on long-short-term memory network (LSTM).

Nucleosome localization is a dynamic process and consists of nucleosome dynamic intervals (NDIs). We preprocessed nucleosome sequence data as time series data (TSD) and developed a long short-term memory network (LSTM) model for training time series data (TSD; LSTM-TSD model) using iterative training and feature learning that predicts NDIs with high accuracy. Sn, Sp, Acc, and MCC of the obtained L...

New-Onset Transient Global Amnesia: A Clinical Challenge in an Air Medical Transportation Pilot With a History of Coronavirus Disease 2019.

A 43-year-old male Bell 214C helicopter pilot presented to the emergency ward with flu-like syndrome. His nasopharyngeal severe acute respiratory syndrome coronavirus 2 real-time polymerase chain reaction test was positive, and a chest computed tomographic scan confirmed coronavirus disease 2019 pneumonia. He was admitted, received treatment, was discharged, and returned to flying. During the miss...

ScoMorphoFISH: A deep learning enabled toolbox for single-cell single-mRNA quantification and correlative (ultra-)morphometry.

Increasing the information depth of single kidney biopsies can improve diagnostic precision, personalized medicine and accelerate basic kidney researc...

The perspectives of older adults with mild cognitive impairment and their caregivers on the use of socially assistive robots in healthcare: exploring factors that influence attitude in a pre-implementation stage.

BACKGROUND: Due to increasing age and an increasing prevalence rate of neurocognitive disorders such as Mild Cognitive Impairment (MCI) and dementia, ...

Leveraging clinical data across healthcare institutions for continual learning of predictive risk models.

The inherent flexibility of machine learning-based clinical predictive models to learn from episodes of patient care at a new institution (site-specif...

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches.

An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was reported to be caused by a novel coronavirus which has ...

Multiclass Classification of Chest X-Ray Images for the Prediction of COVID-19 Using Capsule Network.

It is critical to establish a reliable method for detecting people infected with COVID-19 since the pandemic has numerous harmful consequences worldwi...

Diagnostic accuracy of a commercially available, deep learning-based chest X-ray interpretation software for detecting culture-confirmed pulmonary tuberculosis.

BACKGROUND: Few evaluations of computer-aided detection (CAD) software for analyzing chest radiographs for tuberculosis have used mycobacterial cultur...

Deep learning model for the automatic classification of COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy: a multi-center retrospective study.

This retrospective study aimed to develop and validate a deep learning model for the classification of coronavirus disease-2019 (COVID-19) pneumonia, ...

Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand "ThaiChana".

The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 c...

WVALE: Weak variational autoencoder for localisation and enhancement of COVID-19 lung infections.

BACKGROUND AND OBJECTIVE: The COVID-19 pandemic is a major global health crisis of this century. The use of neural networks with CT imaging can potent...

Study on Integration and Application of Artificial Intelligence and Wireless Network in Piano Music Teaching.

Until 2019, most people had never faced the situation that would be their life-changing moment. Most universities are conducting classes for their stu...

A Deep Learning Approach to Estimate the Incidence of Infectious Disease Cases for Routinely Collected Ambulatory Records: The Example of Varicella-Zoster.

The burden of infectious diseases is crucial for both epidemiological surveillance and prompt public health response. A variety of data, including tex...

Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review.

SARS-CoV-2 (COVID-19) has been one of the worst global health crises in the 21st century. The currently available rollout vaccines are not 100% effect...

Fungal secondary metabolites in food and pharmaceuticals in the era of multi-omics.

Fungi produce several bioactive metabolites, pigments, dyes, antioxidants, polysaccharides, and industrial enzymes. Fungal products are also the prima...

A lightweight CNN-based network on COVID-19 detection using X-ray and CT images.

BACKGROUND AND OBJECTIVES: The traditional method of detecting COVID-19 disease mainly rely on the interpretation of computer tomography (CT) or X-ray...

COVID-19 Spatio-Temporal Evolution Using Deep Learning at a European Level.

COVID-19 evolution imposes significant challenges for the European healthcare system. The heterogeneous spread of the pandemic within EU regions elici...

Decoding the protein-ligand interactions using parallel graph neural networks.

Protein-ligand interactions (PLIs) are essential for biochemical functionality and their identification is crucial for estimating biophysical properti...

Vaccine Therapy in Non-Small Cell Lung Cancer.

Immunotherapy using immune checkpoint modulators has revolutionized the oncology field, emerging as a new standard of care for multiple indications, i...

Beyond technology: Can artificial intelligence support clinical decisions in the prediction of sepsis?

OBJECTIVE: To analyze the critical alarms predictors of clinical deterioration/sepsis for clinical decision making in patients admitted to a reference...