Pneumonia

CT Differentiation and Prognostic Modeling in COVID-19 and Influenza A Pneumonia.

RATIONALE AND OBJECTIVES: This study aimed to compare CT features of COVID-19 and Influenza A pneumonia, develop a diagnostic differential model, and explore a prognostic model for lesion resolution.

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging as a reported concern in vaccinated females. We aimed to develop a machine learning (ML) model to predict post-vaccination AUB in women aged less than 50 years. A large-scale national cohort, the Korean Nationwide Cohort (K-COV-N cohort), was utilized...

Machine Learning-Based Prediction of Postoperative Pneumonia Among Super-Aged Patients With Hip Fracture.

BACKGROUND: Hip fractures have become a significant health concern, particularly among super-aged patients, who were at a high risk of postoperative p...

Application of Artificial Intelligence in Acute Ischemic Stroke: A Scoping Review.

Artificial intelligence (AI) is revolutionizing stroke care by enhancing diagnosis, treatment, and outcome prediction. This review examines 505 origin...

The Promise and Perils of Artificial Intelligence in Advancing Participatory Science and Health Equity in Public Health.

Current societal trends reflect an increased mistrust in science and a lowered civic engagement that threaten to impair research that is foundational ...

[Digital innovations in vaccination communication].

Despite the significant success of vaccinations, increasing vaccine hesitancy poses a threat to public health, making effective vaccination communicat...

SHASI-ML: a machine learning-based approach for immunogenicity prediction in vaccine development.

INTRODUCTION: Accurate prediction of immunogenic proteins is crucial for vaccine development and understanding host-pathogen interactions in bacterial...

Web server-based deep learning-driven predictive models for respiratory toxicity of environmental chemicals: Mechanistic insights and interpretability.

Respiratory toxicity of chemicals is a common clinical and environmental health concern. Currently, most in silico prediction models for chemical resp...

Exploring the response of bacterial community functions to microplastic features in lake ecosystems through interpretable machine learning.

Microplastics (MPs) are ubiquitous and have various characteristics. However, their impacts on bacterial community functions in lakes remain elusive. ...

Unsupervised machine learning clustering approach for hospitalized COVID-19 pneumonia patients.

BACKGROUND: Identification of distinct clinical phenotypes of diseases can guide personalized treatment. This study aimed to classify hospitalized COV...

Community Graph Convolution Neural Network for Alzheimer's Disease Classification and Pathogenetic Factors Identification.

As a complex neural network system, the brain regions and genes collaborate to effectively store and transmit information. We abstract the collaborati...

Machine learning analysis of the relationships between traumatic childbirth experience with positive and negative fertility motivations in Iran in a community-based sample.

BACKGROUND: Psychologically traumatic childbirth leads to short and long-term negative impacts on a woman's health and impacts future reproductive dec...

The use of artificial intelligence to aid the diagnosis of lung cancer - A retrospective-cohort study.

INTRODUCTION: AI software in the form of deep learning-based automatic detection (DLAD) algorithms for chest X-ray (CXR) interpretation have shown suc...

Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.

The vaccinia virus (VV) is extensively utilized as a vaccine vector in the treatment of various infectious diseases, cardiovascular diseases, immunode...

Automated mechanical ventilator design and analysis using neural network.

Mechanical ventilation is the process through which breathing support is provided to patients who face inconvenience during respiration. During the pa...

Utilizing machine learning to predict hospital admissions for pediatric COVID-19 patients (PrepCOVID-Machine).

The COVID-19 pandemic has burdened healthcare systems globally. To curb high hospital admission rates, only patients with genuine medical needs are ad...

A commercial AI tool untrained for COVID-19 demonstrates slight improvement in the interpretation of COVID-19 pneumonia x-rays, especially among inexperienced readers.

INTRODUCTION: Our objective is to evaluate how useful an artificial intelligence (AI) tool is to chest radiograph readers with various levels of exper...

Nanobody screening and machine learning guided identification of cross-variant anti-SARS-CoV-2 neutralizing heavy-chain only antibodies.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to persist, demonstrating the risks posed by emerging infectious diseases to na...

AI Can Be a Powerful Social Innovation for Public Health if Community Engagement Is at the Core.

There is a critical need for community engagement in the process of adopting artificial intelligence (AI) technologies in public health. Public health...

Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.

PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined spec...