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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Evan Scott Shlofmitz, DO, Director of Intravascular Imaging, St. Francis Hospital, in Roslyn, New York, explains how he uses Heartflow's artificial intelligence technology to assess a patient's coronary artery disease from noninvasive CT scans to preplan PCI procedures.

How AI and CCTA help heart teams plan ahead before PCI

Evan Shlofmitz, DO, director of intravascular imaging at St. Francis Hospital, explains how advanced artificial intelligence technology is used to assess a patient's CT scan before they undergo PCI.

radiology dermatology collaboration

Researchers overseas: ‘Radiology has become indispensable to dermatology’

Dermatologists increasingly rely on medical imaging modalities—especially but not solely ultrasound—to help diagnose complex and diverse skin disorders. 

Academic health system working on AI dictation feature for Epic

Chicago-based Rush University System for Health is collaborating with Suki on its development. The two previously partnered on a pilot for an AI clinician assistant, which has since been rolled out across the health system.

Artificial intelligence AI in healthcare

Healthcare AI newswatch: Surgical symphonies, integrated intelligence, generalist AI, more

The surgeon is only one member of a team in the OR. 

primary care provider clinician physician doctor

Primary care is primed for AI. But is AI aligned with primary care?

Fewer than one-third of primary care clinicians have a say in selecting the AI products their institutions expect them to fold into their clinical workflows. That’s a problem. 

Jason Poff, MD, director of innovation deployment for artificial intelligence (AI) at RadPartners, explains the five-step process he uses to evaluate medical imaging AI.

5 steps for evaluating radiology AI applications

Jason Poff, MD, director of innovation deployment for artificial intelligence at Radiology Partners, explains the process he uses to evaluate medical imaging AI. 
 

AI detects subtle changes in images over time.

Adaptable AI system detects subtle changes in imaging, has potential across multiple clinical settings

The Learning-based Inference of Longitudinal imAge Changes, or LILAC, system harnesses machine learning to review medical images that have been collected over a prolonged period.

Good Pixel Smartwatch Loss of Pulse.

FDA clears Google smartwatch tech that calls 911 when a user’s heart stops

Google worked with AI specialists, cardiologists and even stunt performers to develop its new smartwatch feature.

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