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Artificial Intelligence-Enabled Analysis of Public Attitudes on Facebook and Twitter Toward COVID-19 Vaccines in the United Kingdom and the United States: Observational Study.

Journal of medical Internet research
BACKGROUND: Global efforts toward the development and deployment of a vaccine for COVID-19 are rapidly advancing. To achieve herd immunity, widespread administration of vaccines is required, which necessitates significant cooperation from the general...

Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research.

Journal of empirical research on human research ethics : JERHRE
The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their rese...

Current review and next steps for artificial intelligence in multiple sclerosis risk research.

Computers in biology and medicine
In the last few decades, the prevalence of multiple sclerosis (MS), a chronic inflammatory disease of the nervous system, has increased, particularly in Northern European countries, the United States, and United Kingdom. The promise of artificial int...

Explainable automated coding of clinical notes using hierarchical label-wise attention networks and label embedding initialisation.

Journal of biomedical informatics
BACKGROUND: Diagnostic or procedural coding of clinical notes aims to derive a coded summary of disease-related information about patients. Such coding is usually done manually in hospitals but could potentially be automated to improve the efficiency...

Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review.

Journal of medical Internet research
BACKGROUND: More than 17 million people worldwide, including 360,000 people in the United Kingdom, were diagnosed with cancer in 2018. Cancer prognosis and disease burden are highly dependent on the disease stage at diagnosis. Most people diagnosed w...

Early risk assessment for COVID-19 patients from emergency department data using machine learning.

Scientific reports
Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 million estimated deaths worldwide. While epidemiological and clinical character...

Using machine learning improves predictions of herd-level bovine tuberculosis breakdowns in Great Britain.

Scientific reports
In the United Kingdom, despite decades of control efforts, bovine tuberculosis (bTB) has not been controlled and currently costs ~ £100 m annually. Critical in the failure of control efforts has been the lack of a sufficiently sensitive diagnostic te...

Generative models in pathology: synthesis of diagnostic quality pathology images.

The Journal of pathology
Within artificial intelligence and machine learning, a generative model is a powerful tool for learning any kind of data distribution. With the advent of deep learning and its success in image recognition, the field of deep generative models has clea...

Diagnosis and risk stratification in hypertrophic cardiomyopathy using machine learning wall thickness measurement: a comparison with human test-retest performance.

The Lancet. Digital health
BACKGROUND: Left ventricular maximum wall thickness (MWT) is central to diagnosis and risk stratification of hypertrophic cardiomyopathy, but human measurement is prone to variability. We developed an automated machine learning algorithm for MWT meas...