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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cardiovascular emergency ambulance

AI could point first responders to ready, willing and able hospitals in real time

People suddenly stricken with a cardiovascular crisis often survive and recover as long as they’re transported ASAP to a hospital that has two attributes: expertise in emergency heart care and capacity to accommodate the incoming episode.

venture capital corporate suit business corporatization

Private equity healthcare deals hit $90B in 2022, with AI one key 'sector to watch'

Investors continue to pour funds into radiology and other segments of medicine, seeking shelter from volatility seen elsewhere.

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AI predicts the likelihood of a common TAVR complication

Many patients still require a permanent pacemaker following TAVR. In fact, it is more common after TAVR than after surgical aortic valve replacement. 

Example of the four types of breast tissue density. The density of fibroglandular tissue inside the breast impacts the ability to easily see cancers. Cancers are very easy to spot in fatty breasts, but are almost impossible to find in extremely dense breasts. These examples show craniocaudal mammogram findings characterized as almost entirely fatty (far left), scattered areas of fibroglandular density (second from left), heterogeneously dense (second from right), and extremely dense (far right). RSNA

Experts developed a deep learning model that can estimate breast density

When tested, the model achieved a performance comparable to that of human experts.

Coalition for Health AI

Coalition acts to ensure credible, fair, transparent AI in healthcare

Having identified an “urgent” need for guardrails to keep healthcare AI from veering into an avoidable ditch, the Coalition for Health AI has put together a 24-page guide applicable to numerous groups of stakeholders.

The European Society of radiology European Congress of Radiology (ECR) 2023 meeting. Image courtesy of ECR

Key trends in radiology at the European Congress of Radiology 2023 meeting

Bhvita Jani, research manager at the healthcare market analysis firm Signify Research, shares noteworthy happenings from the ECR expo floor.

HeartFlow raises $215M to keep up with growing demand

The company is still riding the momentum of its technology being included in the 2021 American College of Cardiology/American Heart Association chest pain guidelines.

Brain imaging artificial intelligence is a primary area of concentration for AI because oif the critical nature of fast detection and treatment for patients. This is an example of the AI applications displayed by third-party advanced visualization vendor TeraRecon at RSNA 2022.

What is the ROI on AI adoption in radiology?

Radiology makes up the vast majority of FDA-cleared AI algorithms, but with minimal or no reimbursement, hospital administrators may ask whether AI’s value justifies its expense.

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