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: Rusty clinical skills, AI growing up so fast, AI for the malnourished
Clinicians who come to rely on AI for decision support risk the dulling of their skills. The concern is not new. But now comes a pointed call to researchers: Inquire about the particulars of the peril.
Which LLM is best for explaining radiology results?
With patients gaining access to imaging reports earlier than ever, it's critical they have access to large language models that can accurately summarize the results.
Rayus Radiology joins others in offering $40 mammography AI add-on service
The private equity-backed imaging group is initially launching artificial intelligence-enhanced breast imaging at clinics across Washington state.
FDA clears new AI-enabled coronary plaque analysis software
Circle Cardiovascular Imaging, a Canadian medtech company, received the key approval for its cvi42 | Plaque platform.
AI predicts interval cancer risk based on negative mammograms
The ability to predict interval cancer risk is intriguing for providers, as these cancers are often more aggressive and have worse prognoses.

FDA grants Breakthrough Device status to artificial intelligence triage solution from Aidoc

The New York-based radiology vendor announced the news Tuesday, with it applying to a novel product that flags a wide array of life-threatening, time-sensitive conditions in CT scans.

An imaging AI 'epilepsy detective' could help cure treatment-resistant seizures

The tool can identify small focal cortical dysplasia on imaging that is typically missed by radiologists, bottom-of-sulcus dysplasia in particular.

AI triage software significantly reduces radiology report turnaround times, with a caveat

Researchers with the U.S. FDA recently assessed the impact of one such product for pulmonary embolism, with mixed results depending on the time of day.

cybersecurity hacker ransomware cyber data breach

AI-driven medical benefits servicer hit with data breach

Healthcare Interactive confirmed the cyberattack in a statement released last week; however the details have yet to be reported to HHS. The incident happened in July.

AI turns mammograms into CVD risk assessments—no outside data required

Thanks to AI, clinicians can use mammograms to do a lot more than identify signs of breast cancer. Researchers explored data from nearly 50,000 patients, presenting their findings in Heart.

Fewer than 30% of FDA-cleared AI devices share key safety, adverse event info prior to approval

A new analysis is prompting questions regarding how rigorously many of the AI-enabled tools approved by the U.S. Food and Drug Administration are evaluated prior to their clearance.

AI delivers helpful heart health advice—but not every time

AI-powered chatbots can be valuable resources when users have questions about cardiovascular health—but they are still far from perfect.

Does BMI affect AI's accuracy when assessing CT scans?

AI is only as effective as the data it was trained on, and many datasets lack diversity in terms of patient body mass index.

Artificial Intelligence

Healthcare AI today: Rusty clinical skills, AI growing up so fast, AI for the malnourished

Which LLM is best for explaining radiology results?

Rayus Radiology joins others in offering $40 mammography AI add-on service

FDA clears new AI-enabled coronary plaque analysis software

AI predicts interval cancer risk based on negative mammograms