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.

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.
AAA detection gets boost from commercially available AI algorithm
The opportunistic screening helps identify patients in need of monitoring and/or intervention without disrupting workflows.
Healthcare AI today: Senate arguments, aging infrastructure, ‘elastic’ jobs, more
States’ rights or federal power? Senate Republicans are of two minds on AI regulation in the One Big Beautiful Bill.

Stanford researchers find AI may reduce gadolinium dose in MRI scans

Using artificial intelligence (AI), researchers from Stanford University in California have reduced the amount of gadolinium left behind in a patient’s body after an MRI exam, according to research presented at RSNA 2018 in Chicago

RSNA 2018: Vijay Rao wants radiologists to embrace AI

During her speech Sunday, Nov. 25, at the opening session of RSNA 2018 in Chicago, RSNA President Vijay Rao, MD, noted that today's radiologists will be empowered by new technologies, not replaced by them.

RSNA 2018: Behind the scenes at this year's Machine Learning Showcase

Artificial intelligence (AI) is changing how radiologists think about and perform studies, so it’s no surprise AI and machine learning will take center stage this year at RSNA 2018 in Chicago.

RSNA 2018: Radiologists must use AI to create their future

Over the past year, 2018 RSNA President Vijay Rao, MD, has heard radiologists across the globe express their “hype, hope and fear” of the sudden rise in technology. During her presidential address at RSNA's 2018 Annual Meeting in Chicago she put those fears to bed, while placing the onus on radiologists to help do the same.

fMRI-based brain study reveals substance abuse ‘hot spots’

When patients with substance dependence issues are shown cues or images related to such substances, activity in a specific area of the brain increases, according to an fMRI-based study published in Translational Psychiatry. The results may have implications for addiction treatment.

Aidoc, SaferMD partner to offer AI-based solution for increasing MIPS scores

Aidoc and SaferMD are joining forces for a new solution that will use artificial intelligence (AI) to improve clinical results and give radiologists higher Medicare Merit-Based Incentive Payments System (MIPS) scores.

Chest x-ray AI similar, but quicker than radiologists at detecting diseases

A deep learning algorithm showed capability in screening chest x-rays for diseases similar to the interpretations of trained radiologists, but did so in a matter of seconds, according to Stanford University researchers.

AI may help radiologists interpret screening mammography without added reading time

Breast radiologists had slightly higher diagnostic performances when using artificial intelligence (AI) with no additional reading time required, according to a study published Nov. 20 in Radiology.

Artificial Intelligence

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?

AAA detection gets boost from commercially available AI algorithm

Healthcare AI today: Senate arguments, aging infrastructure, ‘elastic’ jobs, more