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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AI and patient care are top of mind for healthcare executives in 2024

C-suite surveyors: AI ‘continues to excite healthcare leaders’

AI and patient care are “top of mind” for healthcare executives in 2024. The pairing seems opportune, since the surveyed leaders see the burgeoning technology as a key tool for improving the perennial mission.

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Patient education materials get boost in readability from generative AI

Ideally, educational pamphlets for patients should be written at a sixth grade reading level, according to the American Medical Association.

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Nearly half of FDA cleared AI medical devices have not been validated on patient data

The FDA’s current draft guidance on the approval process for AI devices does not specify the type of validation the agency recommends manufacturers use. 

Researchers have found that an unexpected combination—artificial intelligence (AI) and a 3D body scanner—can evaluate a person’s metabolic health and identify significant risks of cardiovascular disease, diabetes and other adverse outcomes. In fact, the technique may prove to be more accurate than knowing a person’s body mass index (BMI) or waist-to-hip ratio.

Better than BMI? 3D body scanner uses AI to measure metabolic health

Mayo Clinic specialists have developed a new way to identify risks of cardiovascular disease, diabetes and other adverse outcomes.

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AI draws conclusions from interventional radiology adverse events data, helping docs design interventions

University of Toronto experts analyzed information from the U.S. FDA's database, pinpointing reasons that errors occurred during thermal ablation procedures. 

Dana Smetherman, MD, explains the ACR take on the growing radiology staffing shortage.

Radiology workforce shortage a major concern for the American College of Radiology

Dana H. Smetherman, MD, MBA, CEO of the ACR, discusses the reasons behind the worsening shortage of radiologists, along with possible solutions. 

AISAP, an Israeli healthcare technology company focused on using artificial intelligence (AI) to enhance medical imaging results, has gained U.S. Food and Drug Administration (FDA) clearance for its new point-of-care ultrasound (POCUS) software platform, AISAP Cardio.

FDA clears AI-powered POCUS platform for structural heart disease, heart failure

The cloud-based platform was designed to help even inexperienced users scan and diagnose a majority of common heart issues within minutes without leaving the patient’s side.

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ChatGPT's medical writing is getting so good that it may soon fool AI detectors

The large language model’s medical manuscripts are becoming so well constructed that it can be difficult to distinguish them from those compiled by humans. 

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