9/20/2024
DASI Simulations, OH-based company gained FDA clearance for an artificial intelligence (AI) Product that identifies and measures cardiac structures in CT scans
Reporter: Aviva Lev-Ari, PhD, RN
Israeli vendor AISAP gained FDA clearance for its new AI-enabled, point-of-care ultrasound (POCUS) software platform, AISAP Cardio
Reporter: Aviva Lev-Ari, PhD, RN
JACC editor ‘very important moment’ for Cardiology: New drugs for obesity and prevention, New tools for structural heart analysis for Heart Failure, AI harnessed for Cardiac patient monitoring
Reporter: Aviva Lev-Ari, PhD, RN
7/22/2024
3D Prostate Cancer Estimation Map show “negative margin rate” 45 times greater in AI-detected cases, so the chances of cancer being left behind was far less using Unfold AI technology
The 3D map created by Unfold AI enabled this team to identify precise margins, target the cancerous area and avoid any functional structures of the gland.
SOURCE
Artificial Intelligence detects prostate cancer better than doctors
Prostate Cancer: AI detects 25% greater accuracy than doctors: UCLA study.
4/29/2024
The RoadMap™ – FDA-cleared Roadmap Analysis AI algorithm from HeartFlow: an anatomic visualization to aid clinicians in the interpretation of Coronary computed tomography angiography (CCTA) – Smart CT using AI
AI improves CT assessments, boosts care for real-world heart patients
Dave Fornell | April 26, 2024 | Cardiovascular Business | Artificial Intelligence
Interview with Sarah Jane Rinehart, MD, the director of cardiac imaging at Charleston Area Medical Center, WVA
“I’ve built a protocol around the Roadmap that says every moderate and every severe stenosis should be sent and mild proximal stenosis should be sent, especially if they have high-risk plaque. So the consumer or the ordering physician, no matter who’s reading, will get more consistent results and overall build better confidence in the consumer aspect,” Rinehart said.
She also emphasized the AI’s role in mitigating fatigue-induced oversights and prioritizing cases based on plaque volume and stenosis severity. This can help with workflow. Rinehart added that the integration of plaque analysis expands the scope of assessment beyond luminal stenosis, enabling a more holistic approach to cardiac patient management. This advancement empowers clinicians to tailor medical treatments based on individualized risk profiles, thereby optimizing patient outcomes.
SOURCES
https://www.heartflow.com/roadmap/
4/16/2024
ChatGPT-4 matches radiologists in flagging errors on reports
In addition, GPT-4 required less processing time per radiology report than even the fastest human reader, and the use of GPT-4 resulted in lower mean correction cost per report than the most cost-efficient radiologist, Gertz and Kottlors noted.
The group has been exploring the use of ChatGPT in radiology applications for more than a year, and is “still shocked” by its performance, given that the LLM’s developer OpenAI.com has kept a lid on the data it used to train the model, Gertz said.
The study also suggests that ChatGPT-4 could potentially serve as a teaching tool for residents who might not have access to senior radiologists by providing a “feedback loop” for them to learn from their mistakes, Gertz said.
SOURCE
5/23/2023
A deep learning tool has helped radiologists cut interpretation times by 40%. Developed at the University of Zurich, the software works by quickly bringing up relevant prior exams in reading workflows. This saves radiologists time they would have spent mousing, clicking and scanning. Study published in Academic Radiology, findings summarized in Health Imaging.
SOURCE
From: AI in Healthcare <news@mail.aiin.healthcare>
Reply-To: AI in Healthcare <news@mail.aiin.healthcare>
Date: Tuesday, May 23, 2023 at 9:30 AM
To: Aviva Lev-Ari <avivalev-ari@alum.berkeley.edu>
Subject: Almost half of patients trust AI diagnoses | Healthcare AI names in the news
5/22/2023
THE BOLD AIR SUMMIT
BiOethics, the Law, and Data-sharing: AI in Radiology
Monday, June 12, 2023
(This meeting will be held in-person only)
NYU Langone Health
New York, NY
FOR MEETING INFORMATION & REGISTRATION VISIT:
COURSE DESCRIPTION
Recent years have seen a surge in research at the intersection of artificial intelligence (AI) and medical imaging. Despite numerous publications, translation of this research into real clinical practice has remained elusive. While multiple barriers to implementation exist, this year’s BOLD-AIR Summit aims to specifically present a variety of ethical questions that arise while translating the technology into clinical practice.
Specifically, we will shed light on three primary topics. First, we will discuss the ethical challenges associated with data use in the age of AI in Radiology. Second, we will talk about the ethical questions faced by the payer when reimbursing for AI-driven services. Third, we will discuss ethical barriers to clinical deployment of AI-based devices. We will conclude the Summit by summarizing the day’s findings and synthesizing possible next steps. We hope you’ll be able to join!
This summit is organized by the Departments of Radiology at NYU Grossman School of Medicine and Stanford University School of Medicine.
For more information please contact:
Ana Rejon – ana.rejon@nyulangone.org
SOURCE
From: “Rejon Montero, Ana” <Ana.Rejon@nyulangone.org>
Date: Monday, May 22, 2023 at 8:57 AM
To: “<Undisclosed recipients:;>”
Subject: Reminder – Register Now! 📣 Announcing THE BOLD-AIR SUMMIT! – Monday, June 12 2023 – New York City
4/13/2023
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