Infectious Disease

A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR's) Operating Environment-A Case Study.

The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technologies help designers to meet this demand, as they allow them to abandon classic design and design-testing methods in favor of techniques that do not require the use of real-life systems and thus significantly reduce the costs and time of implementing...

A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.

Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including . We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning model using a publicly accessible tuberculosis dataset. This study was able to reliably detect tuberculosis (TB) from chest X-ray images by utilizing imag...

When Do We Need Massive Computations to Perform Detailed COVID-19 Simulations?

The COVID-19 pandemic has infected over 250 million people worldwide and killed more than 5 million as of November 2021. Many intervention strategies ...

Standard for the Quantification of a Sterilization Effect Using an Artificial Intelligence Disinfection Robot.

Recent outbreaks and the worldwide spread of COVID-19 have challenged mankind with unprecedented difficulties. The introduction of autonomous disinfec...

SUBA-Itraconazole for Primary Antifungal Prophylaxis After Allogeneic Hematopoietic Cell Transplantation.

BACKGROUND: Itraconazole (ITZ) is an effective agent when used as primary invasive fungal disease (IFD) prophylaxis, but is limited by drug tolerabili...

Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge.

BACKGROUND: Delays in patient flow and a shortage of hospital beds are commonplace in hospitals during periods of increased infection incidence, such ...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was ...

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international research...

Determination of probability of causative pathogen in infectious keratitis using deep learning algorithm of slit-lamp images.

Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to det...

Drivers and social implications of Artificial Intelligence adoption in healthcare during the COVID-19 pandemic.

The COVID-19 pandemic continues to impact people worldwide-steadily depleting scarce resources in healthcare. Medical Artificial Intelligence (AI) pro...

Tool for Predicting, Scanning, and Designing Defensins.

Defensins are host defense peptides present in nearly all living species, which play a crucial role in innate immunity. These peptides provide protect...

Accurate classification of Listeria species by MALDI-TOF mass spectrometry incorporating denoising autoencoder and machine learning.

Listeria monocytogenes belongs to the category of facultative anaerobic bacteria, and is the pathogen of listeriosis, potentially lethal disease for h...

Combined deep learning and molecular docking simulations approach identifies potentially effective FDA approved drugs for repurposing against SARS-CoV-2.

The ongoing pandemic of Coronavirus Disease 2019 (COVID-19) has posed a serious threat to global public health. Drug repurposing is a time-efficient a...

Numerical Investigations through ANNs for Solving COVID-19 Model.

The current investigations of the COVID-19 spreading model are presented through the artificial neuron networks (ANNs) with training of the Levenberg-...

A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images.

COVID-19 declared as a pandemic that has a faster rate of infection and has impacted the lives and the country's economy due to forced lockdowns. Its ...

Adrenal Insufficiency in Septic Patients Admitted to Intensive Care Unit: Prevalence and Associated Factors.

Adrenal insufficiency (AI) is associated with an increase in the risk of mortality in ICU-admitted septic patients. It should be suspected not only i...

Machine learning approach for predicting the antifungal effect of gilaburu (Viburnum opulus) fruit extracts on Fusarium spp. isolated from diseased potato tubers.

This work addresses the mathematical model building to detect the diameter of the inhibition zone of gilaburu (Viburnum opulus L.) extract against eig...

Mix Contrast for COVID-19 Mild-to-Critical Prediction.

OBJECTIVE: In a few patients with mild COVID-19, there is a possibility of the infection becoming severe or critical in the future. This work aims to ...

Comparison of drug release behavior of bacterial cellulose loaded with ibuprofen and propranolol hydrochloride.

The aim of this study was to investigate the drug release behavior from bacterial cellulose (BC). Ibuprofen and propranolol hydrochloride were used as...

Estimating hearing aid fitting presets with machine learning-based clustering strategies.

Although there exist nearly 35 × 10 hearing impaired people in the U.S., only an estimated 25% use hearing aids (HA), while others elect not to use pr...