Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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Hospitals in London to start using AI for tasks typically performed by doctors, nurses

A new partnership between University College London Hospitals and the Alan Turing Institute aims to start using artificial intelligence (AI) to perform certain tasks typically carried out by doctors and nurses.

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AI to read 25K CT scans at London hospital for NHS clinical trial

University College London Hospital (UCLH) and the Alan Turing Institute in London have entered a three-year partnership to allow artificial intelligence (AI) to perform a variety of clinical tasks otherwise done by nurses and physicians.

Stakeholders gather in London to discuss development of AI in radiology, oncology

Radiologists, clinical oncologists and industry stakeholders gathered May 16 in London to discuss artificial intelligence (AI) in medical imaging and cancer treatment. The all-day event was organized by the Royal College of Radiologists (RCR) with help from the Alan Turing Institute, Health Data Research UK and the Engineering and Physical Sciences Research Council.

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Experts say AI can lend a helping hand—but radiologists must learn to adapt

In a recent paper from consulting firm Deloitte, experts argue that evolving digital technology—notably artificial intelligence (AI)—has the potential to create jobs in many areas of healthcare, including diagnostic radiology.

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Combination of wearables, AI may help ID onset of cardiovascular disease

Wearable sensors and artificial intelligence (AI) could help predict the onset of cardiovascular disease by assessing an individual's changes in aerobic responses, according to new research published on Feb. 23 in the Journal of Applied Physiology.

Algorithm uses 53 data points to predict life expectancy after heart failure

Researchers from the University of California, Los Angeles (UCLA) have developed an algorithm capable of accurately predicting which patients will survive a heart transplant and for how long.

Machine learning achieves 79% accuracy in identifying long QT syndrome

AliveCor and Mayo Clinic have utilized machine learning to identify long QT syndrome (LQTS), with findings presented at the Heart Rhythm Scientific Sessions in Boston.

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Canadian university receives $3.7M grant for AI digital pathology search engine

The Kimia Lab at the University of Waterloo in Ontario, Canada, announced it has received $3.7 million from the Ontario Research Fund-Research Excellence program for its artificial intelligence (AI) search engine project in digital pathology.