Surveillance

Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak.

Investments in biosecurity practices are made by producers to reduce the likelihood of introducing p...

Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses.

Influenza A viruses are one of the most significant viral groups globally with substantial impacts o...

Statistics versus machine learning: definitions are interesting (but understanding, methodology, and reporting are more important).

Lessons learned from the application of machine learning to studies on plant response to radio-frequency.

This paper applies Machine Learning (ML) algorithms to peer-reviewed publications in order to discer...

Artificial Intelligence for Surveillance in Public Health.

OBJECTIVES: To introduce and summarize current research in the field of Public Health and Epidemiolo...

Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology.

OBJECTIVES: To provide an oveiview of the current application of artificial intelligence (AI) in the...

Performance of an artificial intelligence algorithm for reporting urine cytopathology.

BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automat...

Strategies to Tackle the Global Burden of Diabetic Retinopathy: From Epidemiology to Artificial Intelligence.

Diabetes is a global public health disease projected to affect 642 million adults by 2040, with abou...

Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis.

BACKGROUND: Multiple sclerosis (MS) is a chronic neurological disease occurring mostly in women of c...

Machine learning applications in prostate cancer magnetic resonance imaging.

With this review, we aimed to provide a synopsis of recently proposed applications of machine learni...

Artificial Intelligence for Drug Toxicity and Safety.

Interventional pharmacology is one of medicine's most potent weapons against disease. These drugs, h...

Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.

BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency depa...

A comparison of three data mining time series models in prediction of monthly brucellosis surveillance data.

The early and accurately detection of brucellosis incidence change is of great importance for implem...

Management of Thyroid Nodules Seen on US Images: Deep Learning May Match Performance of Radiologists.

BackgroundManagement of thyroid nodules may be inconsistent between different observers and time con...

Automatic classification of free-text medical causes from death certificates for reactive mortality surveillance in France.

BACKGROUND: Mortality surveillance is of fundamental importance to public health surveillance. The r...

Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning.

Background Coronary CT angiography contains prognostic information but the best method to extract th...

Artificial Intelligence in Medical Education: Best Practices Using Machine Learning to Assess Surgical Expertise in Virtual Reality Simulation.

OBJECTIVE: Virtual reality simulators track all movements and forces of simulated instruments, gener...

An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutri...

Ontology-based specification and generation of search queries for post-market surveillance.

BACKGROUND: The vigilant observation of medical devices during post-market surveillance (PMS) for id...

Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility.

Background Risk stratification systems for thyroid nodules are often complicated and affected by low...

Cancer taxonomy: pathology beyond pathology.

The way we categorise and classify cancer types dictates not only the way we diagnose and treat pati...