Public Health

From tests to truth: A misclassification-aware machine learning framework for estimating brucellosis seroprevalence in wild canids.

Brucellosis is an important zoonotic disease affecting humans, livestock, and wildlife, yet prevalence estimates in wild species are often underestimated due to limited attention to surveillance, as well as insufficient and biased sampling. To clarify exposure patterns in wild canids, we searched PubMed, Scopus, Web of Science, SciELO, and Google Scholar (1962-2025) for primary prevalence studies ...

Machine learning framework for early detection of polio outbreaks from acute flaccid paralysis surveillance data.

Poliomyelitis remains a global public health concern despite remarkable progress toward eradication. The continued circulation of vaccine-derived polioviruses underscores the need for enhanced surveillance systems capable of early detection and rapid response. Acute Flaccid Paralysis (AFP) surveillance, a key component of the polio eradication, plays a vital role in detecting poliovirus transmissi...

Cross-Cultural Differences in Public Discourse on COVID-19 Vaccination in the United States and South Korea: Cross-Sectional Analysis Using Natural Language Processing.

BACKGROUND: The COVID-19 vaccine was introduced as a crucial tool to combat the pandemic. However, concerns about its effectiveness, side effects, and...

Development of machine-learning models to diagnose influenza among international travellers based on symptoms and epidemiological information.

INTRODUCTION: The importation of infectious diseases has increased dramatically in recent years. The diagnosis of such diseases has traditionally been...

Association of surgical resection with survival in retroperitoneal leiomyosarcoma based on SEER propensity score matching and machine-learning models.

Retroperitoneal leiomyosarcoma (RLS) is a rare and aggressive subtype of soft tissue sarcoma with limited population-level evidence guiding surgical d...

Revisiting the social determinants of health with explainable AI: a cross-country perspective.

In social science and epidemiological research, individual risk factors for mortality are often examined in isolation, while approaches that consider ...

Biosensor-based diagnosis for infectious diseases: Nano-enabled revolution.

Infectious diseases (IDs) pose a significant global health threat, exacerbated by the rise of multidrug-resistant (MDR) and antimicrobial-resistant (A...

Reflectance confocal microscopy in the management of lentigo maligna and lentigo maligna melanoma: a systematic review.

BACKGROUND: Lentigo maligna (LM) and lentigo maligna melanoma (LMM) are difficult to manage because of their subclinical extension and ill-defined mar...

AI-enabled wearable microfluidics for next-generation infection monitoring and therapeutics.

Wearable biosensors have revolutionized healthcare by enabling continuous, minimally invasive monitoring of health parameters. While traditional weara...

Social and environmental determinants of Neglected infectious diseases in quilombola communities of the Brazilian Amazon: An epidemiological and machine learning analysis.

Neglected infectious diseases (NIDs) remain a major public health challenge in the Amazon, particularly among quilombola populations living in rural a...

Real-time digital prescriptions unlock influenza dynamics: evidence from 21 million transactions.

Traditional influenza surveillance suffers from 1-2 week reporting delays that compromise outbreak response. We analyzed 21.08 million digital prescri...

Early electrocardiographic repolarization changes are associated with subclinical cancer therapy-related cardiac dysfunction in lymphoma patients: A machine learning-assisted longitudinal study.

UNLABELLED: Anthracycline-induced cardiotoxicity remains a significant clinical challenge. We evaluated longitudinal electrocardiographic (ECG) repola...

Exploring the impact of reimbursement ratios on willingness to vaccinate: A mixed-effects modeling approach using panel data.

Vaccination remains one of the most cost-effective methods for disease prevention. However, utilization of self-paid vaccines, including EV71, varicel...

Toward accurate prediction of pediatric epidemic disease patient volume in the Chaoshan region: A deep learning framework.

Accurate prediction of pediatric epidemic infectious diseases is critical for effective prevention and personalized treatment. Herein, we developed a ...

[Environmental medicine and AI, migration, and emerging and reemerging diseases in Mexico].

Mexico is facing an increasingly challenging health scenario, marked by the resurgence of emerging and re-emerging diseases. This rise is linked to fa...

Predicting metabolic syndrome risk in Chinese adults using integrated features of movement behaviors and dietary intake: a machine learning approach.

BACKGROUND: China is undergoing a rapid nutritional and epidemiological transition. Traditional epidemiological approaches often examine diet and phys...

Hoof lesion detection in lactating Holsteins: Part II. Development and on-farm validation of a predictive classification model using autonomous camera system data compared to passive surveillance.

Hoof lesion detection remains a challenge in lameness management on dairy farms. Recent studies have proposed locomotion score (LS)-based thresholds u...

Inferring crowd crush accidents in typical high-density pedestrian movement zones via the vision-trajectory fusion neural network.

Pedestrian walking constitutes an indispensable mode of daily travel, yet recurrent high-density crowd gatherings in relevant facilities, e.g., holida...

Machine learning approaches to optimize the integration of sociodemographic factors for predicting cancer-specific survival among patients with high-risk prostate cancer.

BACKGROUND: Sociodemographic factors influence the outcomes of prostate cancer (PCa); however, they are rarely incorporated into clinical risk predict...

Potent efficacy of an NA-targeting antibody against a broad spectrum of H5N1 influenza viruses.

For nearly 30 years, Goose/Guangdong-derived highly pathogenic avian influenza H5N1 viruses have posed significant risks to economic stability, food s...