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: 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.
That’s no mere hospital—it’s a ‘complex adaptive system.’ Use GenAI accordingly.
From the perspective of management science, healthcare is a complex adaptive system marked by intricate feedback loops and overlapping interdependencies. As such, the sector demands caution by those introducing large-language AI into its tangled webs.
First AI-enabled POCUS app for detecting pleural effusion and atelectasis earns FDA clearance
The apps are embedded into the Exo Iris transducer, which can be plugged directly into a smartphone, utilized anywhere and without the internet.
Startup seeking to simplify medical imaging referrals raises $101M
Tennr uses an “enterprise orchestration engine” and series of specialized language models, trained on the nuances of processing documentation against payer criteria.
AI model gets helpful heart assessments out of nongated CT scans
"Using AI for tasks like CAC detection can help shift medicine from a reactive approach to the proactive prevention of disease," one researcher said.

YouTube, Robert Downey Jr. team up for original series about AI

YouTube has launched an original series about AI with a little help from one of Marvel’s Avengers.

Researcher awarded $600K grant to study MRI-based ‘GPS maps’ for brain tumors

The concept derives image-based biomarkers from MRI scans to produce a heat map for surgeons to better pinpoint cancers.

‘It transports you to a safe place’: VR helps veterans manage chronic pain

At Tampa-based James A. Haley Veterans Hospital, veterans are being given VR headsets so they can experience a much more relaxing environment, one that isn’t full of pain and discomfort.

MRI scans help researchers predict 10-year breast cancer recurrence

Radiomic analysis can extract mounds of information from MRIs and help researchers determine if a patient’s cancer is likely to return 10 years after treatment.

AI approach may lead to ‘on the fly’ risk scoring for heart attacks

Machine learning is more accurate at predicting the long-term risk of potentially life-threatening cardiac events compared to standard clinical assessments, and eventually may revolutionize cardiovascular care.

How empathy could help AI systems interact with patients

Should AI systems be empathetic? That’s the question asked—and discussed at length—in this new analysis.

AI reads mammograms to better predict breast cancer risk

The deep learning-based model yielded a lower false-negative rate for more aggressive cancers compared to traditional approaches.

FDA grants AI algorithm for heart failure Breakthrough Device designation

Eko, a San Francisco-based healthcare technology company, announced that its ECG-based algorithm for heart failure has been granted a Breakthrough Device designation by the FDA.

Artificial Intelligence

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

That’s no mere hospital—it’s a ‘complex adaptive system.’ Use GenAI accordingly.

First AI-enabled POCUS app for detecting pleural effusion and atelectasis earns FDA clearance

Startup seeking to simplify medical imaging referrals raises $101M

AI model gets helpful heart assessments out of nongated CT scans