Surveillance

Real-time detection and monitoring of public littering behavior using deep learning for a sustainable environment.

With the global population surpassing 8 billion, waste production has skyrocketed, leading to increased pollution that adversely affects both terrestrial and marine ecosystems. Public littering, a significant contributor to this pollution, poses severe threats to marine life due to plastic debris, which can inflict substantial ecological harm. Additionally, this pollution jeopardizes human health ...

MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.

BACKGROUND: Many chemical releases are first noticed by community members, but reporting these concerns often involves considerable hurdles. Artificial Intelligence (AI)-enabled technologies, especially large language models (LLMs), can potentially reduce these barriers.

Bacterial Wastewater-Based Epidemiology Using Surface-Enhanced Raman Spectroscopy and Machine Learning.

Although wastewater-based epidemiology has been used extensively for the surveillance of viral diseases, it has not been used to a similar extent for ...

Association between automatic AI-based quantification of airway-occlusive mucus plugs and all-cause mortality in patients with COPD.

In this cohort study involving 9399 current and former smokers from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease study, we assess...

Artificial intelligence and machine learning in veterinary medicine: a regulatory perspective on current initiatives and future prospects.

The US FDA's Center for Veterinary Medicine (CVM) is advancing its leadership in veterinary science by integrating AI and machine learning (ML) into i...

Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.

Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuab...

The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches fillings.

INTRODUCTION: Accurate measurement of dietary intake without interfering in natural eating habits is a long-standing problem in nutritional epidemiolo...

Noninvasive identification of HER2 status by integrating multiparametric MRI-based radiomics model with the vesical imaging-reporting and data system (VI-RADS) score in bladder urothelial carcinoma.

PURPOSE: HER2 expression is crucial for the application of HER2-targeted antibody-drug conjugates. This study aims to construct a predictive model by ...

Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator.

To create a diagnostic tool before biopsy for patients with prostate-specific antigen (PSA) levels < 20 ng/ml to minimize prostate biopsy-related disc...

Editorial: Mental health, epidemiology and machine learning.

The role of artificial intelligence in pandemic responses: from epidemiological modeling to vaccine development.

Integrating Artificial Intelligence (AI) across numerous disciplines has transformed the worldwide landscape of pandemic response. This review investi...

SVM directed machine learning classifier for human action recognition network.

Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of gu...

Issues and Limitations on the Road to Fair and Inclusive AI Solutions for Biomedical Challenges.

OBJECTIVE: In this paper, we explore the correlation between performance reporting and the development of inclusive AI solutions for biomedical proble...

From Outbreaks to Artificial Intelligence: A Comprehensive Review of Monkeypox Virus Epidemiology, Diagnosis, Treatment, Vaccination, and Deep Learning Applications.

After the global impact of the COVID-19 pandemic, concerns over virus transmission have risen. A state of health emergency was declared in 2022 due t...

Machine learning techniques for the prediction of indoor gamma-ray dose rates - Strengths, weaknesses and implications for epidemiology.

We investigate methods that improve the estimation of indoor gamma ray dose rates at locations where measurements had not been made. These new predict...

Precision in Parsing: Evaluation of an Open-Source Named Entity Recognizer (NER) in Veterinary Oncology.

Integrating Artificial Intelligence (AI) through Natural Language Processing (NLP) can improve veterinary medical oncology clinical record analytics. ...

Clade Ib: a new emerging threat in the Mpox outbreak.

Monkeypox, a zoonotic virus in the , has drawn global attention for its impact on public health. In the current Mpox outbreak, a novel clade, Ib, has ...

Policy brief: Improving national vaccination decision-making through data.

Life course immunisation looks at the broad value of vaccination across multiple generations, calling for more data power, collaboration, and multi-di...

TransformerLSR: Attentive joint model of longitudinal data, survival, and recurrent events with concurrent latent structure.

In applications such as biomedical studies, epidemiology, and social sciences, recurrent events often co-occur with longitudinal measurements and a te...

Mandatory surveillance of bacteremia conducted by automated monitoring.

Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue ...