Public Health & Policy

Suspended particulate matter promotes epithelial-to-mesenchymal transition in alveolar epithelial cells via TGF-β1-mediated ROS/IL-8/SMAD3 axis.

Epidemiological evidence presents that dust storms are related to respiratory diseases, such as pulmonary fibrosis (PF). However, the precise underlying mechanisms of SPM-elicited adverse effects still need to be investigated. Epithelial-mesenchymal transition (EMT) process is a characteristic of PF. We discussed whether suspended particulate matter (SPM) is involved in EMT induction via transform...

An innovative ensemble model based on deep learning for predicting COVID-19 infection.

Nowadays, global public health crises are occurring more frequently, and accurate prediction of these diseases can reduce the burden on the healthcare system. Taking COVID-19 as an example, accurate prediction of infection can assist experts in effectively allocating medical resources and diagnosing diseases. Currently, scholars worldwide use single model approaches or epidemiology models more oft...

PhthisisBioMed Artificial Medical Intelligence: Software for Automated Analysis of Digital Chest X-ray/Fluorograms.

The scope of diagnostic medical examinations increases from year to year causing a reasonable desire to develop and implement new technologies to diag...

Novel fuzzy deep learning approach for automated detection of useful COVID-19 tweets.

Coronavirus (COVID-19) is a newly discovered viral disease from the SARS-CoV-2 family. This has caused a moral panic resulting in the spread of inform...

Comparing the performance of machine learning and conventional models for predicting atherosclerotic cardiovascular disease in a general Chinese population.

BACKGROUND: Accurately predicting the risk of atherosclerotic cardiovascular disease (ASCVD) is crucial for implementing individualized prevention str...

Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression.

Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be effectively reduced by intervening on the risk facto...

A computationally-inexpensive strategy in CT image data augmentation for robust deep learning classification in the early stages of an outbreak.

Coronavirus disease 2019 (COVID-19) has spread globally for over three years, and chest computed tomography (CT) has been used to diagnose COVID-19 an...

Exploring the artificial intelligence "Trust paradox": Evidence from a survey experiment in the United States.

Advances in Artificial Intelligence (AI) are poised to transform society, national defense, and the economy by increasing efficiency, precision, and s...

Individual health-disease phase diagrams for disease prevention based on machine learning.

Early disease detection and prevention methods based on effective interventions are gaining attention worldwide. Progress in precision medicine has re...

Impact of E484Q and L452R Mutations on Structure and Binding Behavior of SARS-CoV-2 B.1.617.1 Using Deep Learning AlphaFold2, Molecular Docking and Dynamics Simulation.

During the outbreak of COVID-19, many SARS-CoV-2 variants presented key amino acid mutations that influenced their binding abilities with angiotensin-...

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism.

The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a severe t...

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.

BACKGROUND: Unintentional injury is the leading cause of death in young children. Emergency department (ED) diagnoses are a useful source of informati...

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19.

According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a significant number of African Americans had been infecte...

Protocol for the automatic extraction of epidemiological information via a pre-trained language model.

The lack of systems to automatically extract epidemiological fields from open-access COVID-19 cases restricts the timeliness of formulating prevention...

New possibilities for medical support systems utilizing artificial intelligence (AI) and data platforms.

In Japan, there is a growing initiative to construct centralized databases and platforms that can aggregate and manage a vast range of medical, health...

Integrating Artificial Intelligence and Wearable IoT System in Long-Term Care Environments.

With the rapid advancement of information and communication technology (ICT), big data, and artificial intelligence (AI), intelligent healthcare syste...

The use of digital health in heart rhythm care.

INTRODUCTION: Digital health is a broad term that includes telecommunication technologies to collect, share and manipulate health information to impro...

Automatic retinoblastoma screening and surveillance using deep learning.

BACKGROUND: Retinoblastoma is the most common intraocular malignancy in childhood. With the advanced management strategy, the globe salvage and overal...

Validation of a Salivary miRNA Signature of Endometriosis - Interim Data.

BACKGROUND: The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early an...

Health system-scale language models are all-purpose prediction engines.

Physicians make critical time-constrained decisions every day. Clinical predictive models can help physicians and administrators make decisions by for...