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. 

Lungs

Lung cancers efficiently identified, characterized with novel AI approach

Researchers at the State University of New York at Stony Brook have demonstrated a deep-learning algorithm that can quickly diagnose early-stage lung cancer on CT scans by combining computerized self-trained tumor identification with engineered identification of specific tumor features.

November 20, 2018
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Viz.ai artificial intelligence stroke software helping doctors win race against time

Sponsored by Viz.ai

The Southeast Regional Stroke Center at Erlanger, based out of the University of Tennessee’s Erlanger Medical Center in Chattanooga, receives referrals from more than 40 hospitals and treats more than 2,500 strokes each year. Patients are rushed to their internationally-recognized center, more commonly referred to as the Erlanger Stroke Network, both day and night, some arriving by ambulance and others by helicopter.

November 20, 2018
As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms needs to undergo quality assurance (QA) reviews. How to validate radiology AI? How can you validate medical imaging AI?

4 areas where AI is having its biggest impact on breast imaging

Artificial intelligence (AI) technologies are advancing at a rapid rate and starting to make a direct impact on breast imaging. There is still a lot of work to be done, however, before AI can truly be trusted with making decisions that may impact a patient’s survival, according to a new commentary published in the American Journal of Roentgenology.

November 16, 2018

Fujifilm to host AI symposium, debut new initiative at RSNA 2018

Fujifilm Medical Solutions USA will host an educational symposium highlighting the influence of artificial intelligence (AI) and present its new AI initiative at RSNA 2018 in Chicago.

November 15, 2018

FDA approves new AI software for brain bleed diagnosis

MaxQ AI’s Accipio Ix intracranial hemorrhage (ICH) detection software has gained FDA clearance, the company announced this week.

November 8, 2018
Artificial intelligence

Why AI models must always be tested on data from outside health systems

Artificial intelligence (AI) tools should always be tested across “a wide range of populations,” according to new research published in PLOS Medicine. The authors shared this warning after seeing some models perform worse when tested on data from an outside health system. 

November 7, 2018

How AI can help overburdened radiologists in China

On average, China has two physicians for every 1,000 people and an upwards of 300 million people suffer from chronic diseases, thereby further burdening an already overworked workforce, according to a news report from digital outlet Brink Asia.

November 6, 2018

AI tool predicts Alzheimer’s more than 6 years ahead of diagnosis

A deep learning algorithm developed using imaging data from more than 1,000 Alzheimer’s disease (AD) patients can accurately predict the presence of AD more than six years before a doctor finalizes a diagnosis, researchers reported in Radiology Nov. 6.

November 6, 2018

Around the web

"This was an unneeded burden, which was solely adding to the administrative hassles of medicine," said American Society of Nuclear Cardiology President Larry Phillips.

SCAI and four other major healthcare organizations signed a joint letter in support of intravascular ultrasound. 

The newly approved AI models are designed to improve the detection of pulmonary embolisms and strokes in patients who undergo CT scans.

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