Surveillance

A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.

Accurate, real-time forecasts of influenza hospitalizations would facilitate prospective resource al...

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted th...

Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data.

Regarding the transportation of people, commodities, and other items, aeroplanes are an essential ne...

Around the EQUATOR With Clin-STAR: AI-Based Randomized Controlled Trial Challenges and Opportunities in Aging Research.

The CONSORT 2010 statement is a guideline that provides an evidence-based checklist of minimum repor...

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global healt...

Pathogen genomic surveillance and the AI revolution.

The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveill...

Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.

DESCRIPTION: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of t...

Digital framework for georeferenced multiplatform surveillance of banana wilt using human in the loop AI and YOLO foundation models.

Bananas (Musa spp.) are a critical global food crop, providing a primary source of nutrition for mil...

Multi-Branch CNN-LSTM Fusion Network-Driven System With BERT Semantic Evaluator for Radiology Reporting in Emergency Head CTs.

The high volume of emergency room patients often necessitates head CT examinations to rule out ische...

Development of a Clinically Applicable Deep Learning System Based on Sparse Training Data to Accurately Detect Acute Intracranial Hemorrhage from Non-enhanced Head Computed Tomography.

Non-enhanced head computed tomography is widely used for patients presenting with head trauma or str...

Rapid detection of carbapenem-resistant Escherichia coli and carbapenem-resistant Klebsiella pneumoniae in positive blood cultures via MALDI-TOF MS and tree-based machine learning models.

BACKGROUND: Bloodstream infection (BSI) is a systemic infection that predisposes individuals to seps...

Empowering PET imaging reporting with retrieval-augmented large language models and reading reports database: a pilot single center study.

PURPOSE: The potential of Large Language Models (LLMs) in enhancing a variety of natural language ta...

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 increa...

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

BACKGROUND: Many chemical releases are first noticed by community members, but reporting these conce...

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 disea...

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 Chro...

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 ...

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...

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. T...

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 <...

Editorial: Mental health, epidemiology and machine learning.