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: $81M acquisition, Illinois says no to AI therapy, AI glucose cleared, more
FDA clears AI-powered glucose monitoring app. The clearance marks a first for an over-the-counter tool in this category.
Data policy research: AI hesitancy remains real, and value-based care models are still an uncertainty
Tech vendor Reveleer and policy analytics firm Mathematica released their 2025 State of Technology in Value-Based Care report, the findings of which show that AI adoption in healthcare is widespread—but integration is spotty.
Imaging-guided surgery startup Method AI raises $20M in Series A financing
Founded in 2021 as a spinoff of the Cleveland Clinic, its platform leverages continuous 3D ultrasound and AI-generated surgical plans to guide robotic-assisted procedures.
Healthcare AI today: 95% fail rate, epic at Epic, AI to the rescue of short staffs, more
Most organizations trying out generative AI—a full 95%—are failing to receive a measurable return on the pilot investment.
Johns Hopkins researchers: Time is running out to leverage AI for patients beyond a certain age
If three sticking points aren’t unstuck soon, older Americans won’t benefit much by the 1,000+ medical devices that, as of 2025, are both equipped with AI and cleared by the FDA.

3D MRI may surpass 2D for detecting knee cartilage defects

Technological advancements over the past three decades have placed 3D MRI on par with its 2D counterpart in depicting cartilage defects, according to a study published in Radiology. With specific alterations, the modality may be able to replace traditional MRI.

AI could protect public health by monitoring water treatment systems

Artificial intelligence (AI) is proving valuable across the healthcare spectrum—from helping radiologists screen for disease to predicting difficulties during surgery. Researchers now hope the cutting-edge technology could safeguard public health by monitoring large-scale water treatment operations.

Ohio radiologist says AI won't wipe out the profession anytime soon

Plenty of warnings have been offered about radiology's impending doom thanks to artificial intelligence (AI). Phil Shaffer, a radiologist at Riverside Radiology and Interventional Associates in Columbus, Ohio, offered a response with an opinion piece in The Scientist.

AI in radiology: 3 key ethical issues the specialty must address

As the influence of artificial intelligence (AI) continues to grow in radiology, the specialty must come together to re-examine its ethics and code of behavior, according to a new commentary published in the Journal of the American College of Radiology.

AI needs ethical standards, but are radiologists ready?

Artificial intelligence (AI) is becoming an essential part of radiology, meaning the industry must consider ethics for computers and AI, according to an opinion piece by Marc Kohli, MD, and Raym Geis, MD, published July 15 in the Journal of the American College of Radiology.

Machine learning IDs schizophrenia via MRI with 78% accuracy

A machine learning algorithm trained to analyze MRI images identified schizophrenia patients with 78 percent accuracy, according to a recent study published in Molecular Psychiatry.

SPECT imaging may help guide future HIV treatment

Researchers used single-photon emission computed tomography (SPECT) to assess the immune system recovery of macaque monkeys with an HIV-like infection. The work may help researchers understand recovery in humans after HIV treatment.

CAD system uses deep learning to detect, segment, classify masses from mammograms

Researchers have developed a fully integrated computer-aided diagnosis (CAD) system that detects, segments and classifies masses from mammograms using deep learning and a deep convolutional neural network (CNN), according to a new study published by the International Journal of Medical Informatics.

Artificial Intelligence

Healthcare AI today: $81M acquisition, Illinois says no to AI therapy, AI glucose cleared, more

Data policy research: AI hesitancy remains real, and value-based care models are still an uncertainty

Imaging-guided surgery startup Method AI raises $20M in Series A financing

Healthcare AI today: 95% fail rate, epic at Epic, AI to the rescue of short staffs, more

Johns Hopkins researchers: Time is running out to leverage AI for patients beyond a certain age