Royal Philips will debut its latest AI-enabled cardiovascular ultrasound platform at the European Society of Cardiology (ESC) 2024 Congress to be held August 30 to September 2 in London, as well as highlight new ultrasound technology.
The platform includes automated AI heart assessment tools and has been integrated with the company’s EPIQ CVx and Affiniti CVx cardiovascular ultrasound scanners. The new applications include the industry’s first automated tool for segmental wall motion scoring of the heart to quickly identify disorders including coronary artery disease and cardio-oncology issues, Philips said.
The applications also enable fully automated 3D quantification of mitral regurgitation (MR) volumes, which can help clinicians perform more efficient analysis of patients with heart valve disease, the company added.
Also making its debut at ESC 2024 is the company’s new mini ultrasound transducer X11 4t, which was launched earlier this year, Philips said. The transducer is compatible with the company’s EPIQ CVx ultrasound system and expands access to care for more patients, including the smallest undergoing complex intracardiac procedures like valve repairs, Philips said.
In a news release on its ESR 2024 highlights, Philips noted that according to a recent global survey it conducted, 75% of cardiology leaders reported that staff shortages are negatively impacting patient care within their organizations. The survey included 3,000 healthcare leaders across 14 countries, with 40% of respondents also indicating that their organizations plan to invest in generative AI in the next 12 months, according to the company.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
