Flu & URI

Development and assessment of an assisted diagnosis model using machine learning for identifying adult-onset Still's disease in fever of unknown origin: a retrospective study in China.

BACKGROUND: Adult-onset Still's disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic criterion. OBJECTIVE: To develop and validate a clinically applicable model for identifying AOSD among patients with fever of unknown origin (FUO) who have clinical suspicion for AOSD. METHODS: Clinical data (2010-2020) were divided into training and internal test set (7:3) usi...

Pangenome-guided immunoinformatics design and in silico characterization of a multi-epitope vaccine candidate against Acinetobacter baumannii with nanoparticle assembly potential.

Acinetobacter baumannii is a critical multidrug-resistant pathogen causing severe healthcare infections with high mortality, yet no licensed vaccine exists. This study aims to identify universally conserved surface antigens through pangenome analysis, predict immunogenic epitopes using integrated machine learning, and computationally design and in silico characterize a self-assembling nanoparticle...

Interpretable machine learning model of contrast-enhanced CT radiomics for predicting post-BCG recurrence in high-grade non-muscle-invasive bladder cancer.

BACKGROUND AND PURPOSE: While intravesical Bacillus Calmette-Guérin Vaccine (BCG) instillation remains standard adjuvant therapy for high-grade non-mu...

AI-assisted versus manual sustainability assessment of a high-throughput LC-MS/MS method for psychotropic and OTC drugs of abuse in human plasma.

A rapid, sensitive, and selective LC-MSMS method was developed and validated for the quantification of dextromethorphan (DXM), pseudoephedrine (PSE), ...

A population-based retrospective machine learning study of COVID-19 severity using integrated clinical and viral genomic data in Jiangsu Province, China.

BACKGROUND: As coronavirus disease 2019 (COVID-19) has transitioned into an endemic phase characterized by sustained transmission and widespread hybri...

Factors associated with delayed diagnosis of fibrotic interstitial lung disease: a retrospective cohort study.

BACKGROUND: Timely diagnosis and treatment of fibrotic interstitial lung disease (ILD) is crucial to preserve lung function and limit healthcare costs...

Physics-guided framework for climate dependent disease prediction: coupling compartment model with deep learning.

BACKGROUND: Influenza-like illness (ILI) serves as a representative climate dependent disease due to its climate sensitivity, widespread transmission,...

New approach methodologies (NAMs) for preclinical and translational evaluation of mRNA-lipid nanoparticle (LNP) therapeutics.

Messenger RNA-lipid nanoparticle (mRNA-LNP) therapeutics have emerged as a versatile drug modality, enabling in vivo protein expression for vaccines, ...

Diagnostic challenges in re-emerging rickettsioses: why current tools fall short.

SUMMARYRickettsial diseases, encompassing scrub typhus, spotted fever group rickettsioses, and typhus group rickettsioses, represent a significant and...

The Development Path of Gynecological Cytology after Papanicolaou: from Bethesda to Artificial Intelligence and Personalized Medicine.

BACKGROUND: Cervical cancer is the fourth most common cancer whose incidence was significantly reduced with the help of Pap smear and organized cervic...

A large-scale single-cell atlas reveals the pulmonary immune panorama in adult patients with influenza.

RATIONALE: The host immune determinants that distinguish protective from life-threatening responses to influenza are poorly understood. Identifying dr...

Findings from the 2025 AMCP Foundation Symposium: Health Optimization 2.0.

The 2025 AMCP Foundation Symposium: Health Optimization 2.0 convened a select group of just over 70 managed care stakeholders in Dallas, Texas, on Dec...

An Explainable Machine Learning Model for Early Prediction of Incident Myocardial Injury in Patients With Severe Fever With Thrombocytopenia Syndrome.

This study aimed to develop an explainable machine learning-based model to enable early prediction of incident myocardial injury during hospitalizatio...

Deep learning enables rabies virus detection and antibody quantification in cell culture.

Rabies remains a major neglected disease, causing tens of thousands of deaths annually in endemic regions. Cell culture-based assays are central to ra...

Climate variability and COVID-19 non-pharmaceutical interventions shaped dengue transmission in Guangdong: an integrated modeling study.

Dengue fever is a major climate-sensitive mosquito-borne disease shaped by both environmental conditions and human behavior. We quantified the combine...

Machine learning-based prediction of ICU admission and mortality in Crimean-Congo hemorrhagic fever by using wide-range targeted metabolomics.

PURPOSE: This study aimed to evaluate the potential of amino-acid profiles to predict disease progression in patients with Crimean-Congo Hemorrhagic F...

Artificial intelligence in rheumatology: a cross-sectional Scopus-based analysis.

Artificial intelligence (AI) is increasingly used in clinical medicine. Rheumatology is well-suited to AI applications due to diagnostic complexity of...

A Novel Machine Learning Approach for Predicting Prognosis of SFTS Patients in the Early Stages of Disease.

OBJECTIVE: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne disease characterized by high morbidity and mortality rates. T...

A computational method to design broad-spectrum T cell-inducing vaccines applied to Betacoronaviruses.

Antigenically diverse pathogens such as coronaviruses pose substantial global health threats, highlighting the need for broad-spectrum vaccines. Here,...

Artificial intelligence-enhanced nurse navigation for monitoring and care of long COVID.

INTRODUCTION: Long COVID is a multisystem condition with challenging diagnosis. Nurse-navigation, a patient-centered intervention, can enhance educati...