Infectious Disease

Optimizing non-pharmaceutical intervention strategies against COVID-19 using artificial intelligence.

One key task in the early fight against the COVID-19 pandemic was to plan non-pharmaceutical interventions to reduce the spread of the infection while limiting the burden on the society and economy. With more data on the pandemic being generated, it became possible to model both the infection trends and intervention costs, transforming the creation of an intervention plan into a computational opti...

Rational design of stapled antimicrobial peptides.

The global increase in antimicrobial drug resistance has dramatically reduced the effectiveness of traditional antibiotics. Structurally diverse antibiotics are urgently needed to combat multiple-resistant bacterial infections. As part of innate immunity, antimicrobial peptides have been recognized as the most promising candidates because they comprise diverse sequences and mechanisms of action an...

A deep learning approach reveals unexplored landscape of viral expression in cancer.

About 15% of human cancer cases are attributed to viral infections. To date, virus expression in tumor tissues has been mostly studied by aligning tum...

Logistic regression technique is comparable to complex machine learning algorithms in predicting cognitive impairment related to post intensive care syndrome.

To evaluate the performance of machine learning (ML) models and to compare it with logistic regression (LR) technique in predicting cognitive impairme...

Spatial and deep learning analyses of urban recovery from the impacts of COVID-19.

This study investigates urban recovery from the COVID-19 pandemic by focusing on three main types of working, commercial, and night-life activities an...

Prediction models for the impact of the COVID-19 pandemic on research activities of Japanese nursing researchers using deep learning.

AIM: This study aimed to construct and evaluate prediction models using deep learning to explore the impact of attributes and lifestyle factors on res...

Researchers turn to tiny robots to fight antibiotic resistance.

Effect of robot-assisted stair climbing training as part of a rehabilitation program to improve pulmonary function, gait performance, balance, and exercise capacity in a patient after severe coronavirus disease 2019: a case report.

BACKGROUND: Severe coronavirus disease 2019 (COVID-19) infection may decrease respiratory and physical functions.

Artificial intelligence-based tools applied to pathological diagnosis of microbiological diseases.

Infectious diseases still threaten the global community, especially in resource-limited countries. An accurate diagnosis is paramount to proper patien...

Nurses' perception towards care robots and their work experience with socially assistive technology during COVID-19: A qualitative study.

This study aimed to explore nurses' perceptions towards care robots and their work experiences in caring for older adults who use socially assistive t...

Deep Learning Solution for Quantification of Fluorescence Particles on a Membrane.

The detection and quantification of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus particles in ambient waters using a membrane-ba...

A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B.

OBJECTIVE: To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode imag...

Identification of Active Pulmonary Tuberculosis Among Patients With Positive Interferon-Gamma Release Assay Results: Value of a Deep Learning-based Computer-aided Detection System in Different Scenarios of Implementation.

PURPOSE: To evaluate the accuracy of a deep learning-based computer-aided detection (CAD) system in identifying active pulmonary tuberculosis on chest...

CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images.

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first-line imaging technique for...

Autonomous Swallow Segment Extraction Using Deep Learning in Neck-Sensor Vibratory Signals From Patients With Dysphagia.

Dysphagia occurs secondary to a variety of underlying etiologies and can contribute to increased risk of adverse events such as aspiration pneumonia a...

Lung Diseases Detection Using Various Deep Learning Algorithms.

The primary objective of this proposed framework work is to detect and classify various lung diseases such as pneumonia, tuberculosis, and lung cancer...

Socially assistive robots in health and social care: Acceptance and cultural factors. Results from an exploratory international online survey.

AIM: This study explored the views of an international sample of registered nurses and midwives working in health and social care concerning socially ...

Multi-objective optimization determines when, which and how to fuse deep networks: An application to predict COVID-19 outcomes.

The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 si...

Models and data of AMPlify: a deep learning tool for antimicrobial peptide prediction.

OBJECTIVES: Antibiotic resistance is a rising global threat to human health and is prompting researchers to seek effective alternatives to conventiona...

Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.

BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research i...