Surveillance

SEINN: A deep learning algorithm for the stochastic epidemic model.

Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamic...

Practical considerations for specifying a super learner.

Common tasks encountered in epidemiology, including disease incidence estimation and causal inferenc...

Co-evolution of epidemiology and artificial intelligence: challenges and opportunities.

Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry).

US Quantification of Liver Fat: Past, Present, and Future.

Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardi...

Scoping Review: Legal and Ethical Principles of Artificial Intelligence in Public Health.

The growing accessibility of large health datasets and AI's ability to analyze them offers significa...

Applications of machine learning in animal and veterinary public health surveillance.

Machine learning (ML) is an approach to artificial intelligence characterised by the use of algorith...

Personal Data for Public Benefit: The Regulatory Determinants of Social Licence for Technologically Enhanced Antimicrobial Resistance Surveillance.

Technologically enhanced surveillance systems have been proposed for the task of monitoring and resp...

DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology.

DECIDE-AI is a new, stage-specific reporting guideline for the early and live clinical evaluation of...

[Applications of digital medical techniques for dental dysplasia].

Dental dysplasia are abnormalities in teeth structure, morphology, number and eruption caused by gen...

Natural language processing in narrative breast radiology reporting in University Malaya Medical Centre.

Radiology reporting is narrative, and its content depends on the clinician's ability to interpret th...

A novel method for conformity assessment testing of electrocardiographs for post-market surveillance purposes.

BACKGROUND: Monitoring cardiac parameters is the fundamental aspect of every diagnostic process and ...

A novel method for conformity assessment testing of infant incubators for post-market surveillance purposes.

BACKGROUND: Premature born infants or infants born sick require immediate medical attention and decr...

[Literacy for Appropriate Use of Medical Big Data and Artificial Intelligence].

Recent developments have enabled daily accumulated medical information to be converted into medical ...

[Application and development of voice analysis and endoscopic technology combined with artificial intelligence in the diagnosis and treatment of throat disease].

In the diagnosis and treatment of throat disease, the application and development of combining voice...

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.

Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the ...

Machine Learning Approach to Facilitate Knowledge Synthesis at the Intersection of Liver Cancer, Epidemiology, and Health Disparities Research.

PURPOSE: Liver cancer is a global challenge, and disparities exist across multiple domains and throu...

Impact of computational approaches in the fight against COVID-19: an AI guided review of 17 000 studies.

SARS-CoV-2 caused the first severe pandemic of the digital era. Computational approaches have been u...

Towards gender equity in artificial intelligence and machine learning applications in dermatology.

There has been increased excitement around the use of machine learning (ML) and artificial intellige...

Electronic surveillance of patient safety events using natural language processing.

OBJECTIVE: We describe our approach to surveillance of reportable safety events captured in hospital...

Deep Learning for Outcome Prediction in Neurosurgery: A Systematic Review of Design, Reporting, and Reproducibility.

Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predi...