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.

AI turns low-quality MRI scans into helpful heart images
A team of biomedical engineers, radiologists and cardiologists has developed a new AI model capable of restoring low-quality cardiac MRI scans.
New AI-enabled, helium-free MRI system earns FDA clearance
The scanner requires just 0.7 liters of liquid helium for cooling—a fraction of the more than 1,500 liters standard systems need to operate safely.
Healthcare AI today: Bipartisan AI policy guidance, AI claims denials, LLM brain rot, more
Federal lawmakers have a fresh resource to keep them up on healthcare AI that falls outside of formal FDA oversight. It comes in the form of a new report from the nonprofit Bipartisan Policy Center.
Common features of breast cancers missed by AI
Imaging experts advocate for “meticulous assessments” of cases that include luminal cancer, dense breasts, and lesions located outside the mammary zone, among other factors.
Why do AI-savvy consumers harbor skepticism toward medical AI?
Patients who frequently use AI tend to readily trust AI-assisted diagnoses made by their physicians. Counterintuitively, however, those who would rank themselves among the very best-informed about AI tend to mistrust such diagnoses.

Deep-learning platform detects malignant nodules on x-ray, beating radiologists

A deep learning-based automatic detection algorithm (DLAD) detected malignant pulmonary nodules on chest x-rays better than radiologists, according to a Sept. 25 study in Radiology.

iPhone medical ultrasound device startup raises $250 million

The Butterfly Network, makers of the innovative iPhone ultrasound-on-chip named Butterfly iQ, announced it has raised $250 million to start shipping to 40 million healthcare practitioners globally, according to a report published Sept. 26 by Business Insider.

4D CT could supplement wrist radiographs in evaluating radioulnar deviation

For patients with wrist movement abnormalities, four-dimensional CT imaging during radioulnar deviation could improve diagnosis of suspected scapholunate ligament tears and injuries, according to research published online Sept. 25 in Radiology.

Sloan Kettering’s deal with digital pathology startup draws backlash

An agreement between artificial intelligence (AI) startup Paige.AI and Memorial Sloan Kettering Cancer Center in New York is drawing backlash over the company’s exclusive rights to the cancer center’s 25 million pathology slide images, the New York Times reported.

Memorial Sloan Kettering fundraising campaign won’t focus on utilizing AI in cancer treatments

A cancer center’s fundraising campaign will no longer focus on the use of artificial intelligence (AI) in cancer treatments following accusations it commercialized the work of employees for private gain, according to a report by The New York Times and ProPublica.

Deep learning algorithm detects malignant pulmonary nodules better than radiologists

Researchers have developed a deep learning-based automatic detection algorithm (DLAD) that can detect malignant pulmonary nodules on chest x-rays better than physicians, sharing their findings in a new study published by Radiology.

CT technique offers microscopic view of Egyptian remains

Swedish researchers have used a novel CT imaging technique to study the soft tissue of an ancient Egyptian mummy’s hand at microscopic levels, according to a Sept. 25 study published in Radiology.

Unused MRI information offers insights into brain conditions

MRI scans produce mounds of unused data. Now, researchers at Washington University School of Medicine in St. Louis have created a new method of utilizing that information to determine how many and where cells have been lost due to injury or disease.

Artificial Intelligence

AI turns low-quality MRI scans into helpful heart images

New AI-enabled, helium-free MRI system earns FDA clearance

Healthcare AI today: Bipartisan AI policy guidance, AI claims denials, LLM brain rot, more

Common features of breast cancers missed by AI

Why do AI-savvy consumers harbor skepticism toward medical AI?