Vaccines

Multi-regional radiomics based on planning CT and information complementarity between GTVp and GTVn: an explainable model for predicting 5-year recurrence risk in HPV-positive oropharyngeal cancer.

PURPOSE: This study aims to develop and validate a multi-regional radiomics machine learning model integrating the spatial heterogeneity features of both the primary gross tumor volume (GTVp) and metastatic lymph nodes (GTVn) to explore its potential as a non-invasive tool for estimating the 5-year recurrence risk of HPV-positive oropharyngeal carcinoma (OPC) patients. METHODS: This study included...

Virus infections and cancers: from mechanisms to therapeutics.

Viral infections are a major contributor to global cancer incidence and mortality. However, integrative reviews that connect viral classification, carcinogenic mechanisms, tumor microenvironment remodeling, and translational strategies remain limited. This review summarizes the classification and epidemiological characteristics of major oncogenic viruses, including human papillomavirus (HPV), Epst...

Predicting COVID-19 severity using machine learning: the role of clinical parameters, blood groups, and vaccination status across age groups.

OBJECTIVES: COVID-19 has had strong impacts on both global health systems and economies. Therefore, understanding disease severity and progression is ...

AI Meets Attitudes: Cross-Sectional Quantitative Study of COVID-19 Vaccine Hesitancy in Alaska's Diverse Communities.

BACKGROUND: The global COVID-19 vaccine rollout faces challenges from persistent hesitancy, especially in rural and underserved regions. Alaska's uniq...

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 e...

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...

AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.

BACKGROUND: Neoantigens-tumor-specific peptides generated by somatic mutations-are central targets of effective anticancer T cell immunity and underpi...

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, ...

Leveraging multimodal cancer immunotherapy to amplify the efficacy of oncolytic viruses.

Oncolytic viruses (OVs) represent a versatile platform for cancer immunotherapy, capable of selectively infecting and lysing tumor cells while trigger...

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...

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...

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...

CIST: A clade-informed sequence transformer framework for predicting influenza virus antigenicity.

Rapid antigenic evolution of influenza viruses complicates timely vaccine strain selection and renders prospective interpretation of serological assay...

Augmenting Pediatric Care With Artificial Intelligence: Opportunities and Responsibilities for Nurse Practitioners.

BACKGROUND: Artificial intelligence (AI) is emerging as a critical tool for nurse practitioners delivering pediatric and adolescent and young adult (A...

Neural networks and behavioral frameworks to analyse the impact of media and individual awareness for controlling epidemics.

Enhancing individual awareness and immunization are generally recognized as fundamental strategies for controlling infectious diseases. Awareness is i...

A fractional ABC model for hepatitisB virus transmission with forecasting of epidemic trends using neural networks.

This paper develops a fractional-order HBV epidemic model using the Atangana-Baleanu-Caputo (ABC) fractional derivative with a nonsingular Mittag-Leff...

Artificial intelligence in cervical cancer screening and triage: a role-stratified systematic review and bivariate meta-analysis.

PURPOSE OF REVIEW: Artificial intelligence (AI) tools for cervical cancer screening have proliferated, but modality-pooled accuracy estimates conflate...

Blood-based Biomarkers in Cervical Cancer: The Emerging Role of Circulating Human Papillomavirus and Tumor Deoxyribonucleic Acid.

Cervical cancer (CC) remains a major global health burden, particularly in low- and middle-income countries (LMICs), where access to timely diagnosis ...

Public antibody clonotypes and deep learning identify SARS-CoV-2 and HIV broadly neutralizing antibodies in immune repertoires.

Broadly neutralizing antibodies (bnAbs) are essential for the development of vaccines and therapeutics against rapidly evolving pathogens like HIV and...