HDAI Unveils Real-Time AI Chart Summaries at HLTH 2025

October 20, 2025
Health Data Analytics Institute announced the general availability of its real-time, EHR-embedded AI chart summaries at HLTH 2025 in Las Vegas, expanding its HealthVision platform for clinicians managing complex patient records.

Health Data Analytics Institute (HDAI) announced the general availability of its real-time, EHR-embedded AI chart summaries at the HLTH 2025 conference in Las Vegas, according to a press release. The new capability extends HDAI’s HealthVision platform, which integrates predictive models and large language model-based chart summarization to assist clinicians in identifying patient risks and care priorities.

The AI chart summaries synthesize extensive patient records into concise overviews, helping healthcare providers manage complex cases such as heart failure, advanced illness, and palliative care. The tool is already in use at several major academic medical centers, supporting care coordination and operational processes like discharge planning and nutrition assessment.

Nassib Chamoun, HDAI’s CEO, presented the announcement during a panel titled “Crystal Ball Medicine” at HLTH, alongside representatives from Northwell Health, the American Heart Association, and Aidoc. The discussion focused on how predictive analytics can help healthcare organizations reduce unplanned admissions, post-discharge mortality, and other adverse outcomes.

HealthVision combines hundreds of predictive models with real-time data analysis to generate one-page AI summaries within electronic health records, aiming to streamline clinical decision-making and improve efficiency across health systems.

We hope you enjoyed this article.

Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.

Also, consider following us on social media:

Subscribe to Life AI Weekly

Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more