Public Health

Enhancing Postmarketing Surveillance of Medical Products With Large Language Models.

IMPORTANCE: The Sentinel System is a key component of the US Food and Drug Administration (FDA) postmarketing safety surveillance commitment and uses clinical health care data to conduct analyses to inform drug labeling and safety communications, FDA advisory committee meetings, and other regulatory decisions. However, observational data are frequently deemed insufficient for reliable evaluation o...

An architecture for COVID-19 analysis and detection using big data, AI, and data architectures.

The COVID-19 epidemic is affecting individuals in many ways and continues to spread all over the world. Vaccines and traditional medical techniques are still being researched. In diagnosis and therapy, biological and digital technology is used to overcome the fear of this disease. Despite recovery in many patients, COVID-19 does not have a definite cure or a vaccine that provides permanent protect...

Description and Validation of a Novel AI Tool, LabelComp, for the Identification of Adverse Event Changes in FDA Labeling.

INTRODUCTION: The accurate identification and timely updating of adverse reactions in drug labeling are crucial for patient safety and effective drug ...

The Relationship Between Metal Exposure and HPV Infection: Evidence from Explainable Machine Learning Methods.

HPV is a ubiquitous pathogen implicated in cervical and other cancers. Although vaccines are available, they do not encompass all subtypes. Meanwhile,...

Prevalence of Avian Influenza Virus in Atypical Wild Birds Host Groups during an Outbreak of Highly Pathogenic Strain EA/AM H5N1.

The global outbreak of highly pathogenic avian influenza (HPAI) H5N1 Eurasian lineage goose/Guangdong clade 2.3.4.4b virus that was detected in North ...

COVID-19 prevention and control effect of non-pharmaceutical interventions-fuzzy-sets qualitative comparative analysis based on 69 countries in the world.

INTRODUCTION: Coronavirus disease 2019 occurred unexpectedly in late December 2019, it was difficult to immediately develop an effective vaccine or pr...

Biomedical Data Science, Artificial Intelligence, and Ethics: Navigating Challenges in the Face of Explosive Growth.

Advances in biomedical data science and artificial intelligence (AI) are profoundly changing the landscape of healthcare. This article reviews the eth...

Opportunities and shortcomings of AI for spatial epidemiology and health disparities research on aging and the life course.

Established spatial and life course methods have helped epidemiologists and health and medical geographers study the impact of individual and area-lev...

A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.

BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical co...

MGLEP: Multimodal Graph Learning for Modeling Emerging Pandemics with Big Data.

Accurate forecasting and analysis of emerging pandemics play a crucial role in effective public health management and decision-making. Traditional app...

Leveraging artificial intelligence in vaccine development: A narrative review.

Vaccine development stands as a cornerstone of public health efforts, pivotal in curbing infectious diseases and reducing global morbidity and mortali...

Predictive Modeling of Long-Term Prognosis After Resection in Typical Pulmonary Carcinoid: A Machine Learning Perspective.

Typical Pulmonary Carcinoid (TPC) is defined by its slow growth, frequently necessitating surgical intervention. Despite this, the long-term outcomes ...

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of resea...

Computationally intelligent real-time security surveillance system in the education sector using deep learning.

Real-time security surveillance and identity matching using face detection and recognition are central research areas within computer vision. The clas...

Vaccine design and development: Exploring the interface with computational biology and AI.

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to ...

Causal inference and machine learning in endocrine epidemiology.

With the rapid development of computer science, there is an increasing demand for the use of causal inference methods and machine learning in the rese...

Artificial intelligence for detection of prostate cancer in biopsies during active surveillance.

OBJECTIVES: To evaluate a cancer detecting artificial intelligence (AI) algorithm on serial biopsies in patients with prostate cancer on active survei...

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods.

BACKGROUND: Nosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term,...

The implementation of robotic dogs in automatic detection and surveillance of red imported fire ant nests.

BACKGROUND: The Red Imported Fire Ant (RIFA), scientifically known as Solenopsis invicta, is a destructive invasive species causing considerable harm ...

Modeling and control of COVID-19 disease using deep reinforcement learning method.

The prevalence of epidemics has been studied by researchers in various fields. In the last 2 years, the outbreak of COVID-19 has affected the health, ...