New Clinical Data Supports Viz.ai Solution for Improved Pulmonary Embolism Detection and Care Coordination

Company’s Artificial Intelligence Technology Shows Better Results in Early Detection and Patient Care

Excerpt from the Press Release:

SAN FRANCISCO–(BUSINESS WIRE)–Viz.ai, the leader in AI-powered disease detection and intelligent care coordination, today announced new clinical data supporting advancements in pulmonary embolism (PE) detection. Two studies have demonstrated the real-world clinical efficacy of Viz.ai’s PE Module to quickly and accurately identify PE and associated right heart strain, accelerate care coordination, and improve healthcare workflow efficiency. Pulmonary embolism is a severe medical condition, which affects around 900,000 people in the U.S. every year, and often challenging to diagnose and treat due to overlapping symptoms with other diseases.

The first study, “Automated PE Clot Detection and RV/LV Ratio Measurement using AI-based Deep Learning Algorithms: A Preliminary Validation Study,” evaluated the performance of Viz PE and Viz Right Ventricle/Left Ventricle (RV/LV) algorithms. The study found that, across 100 retrospectively-collected chest CTPA images, Viz PE demonstrated a sensitivity of 91.1% and specificity of 100.0%. Furthermore, the study revealed a significant positive correlation between algorithmic and manual calculation of RV/LV ratio.

“Our preliminary findings underscore the remarkable performance of Viz PE and Viz RV/LV,” said Parth Rali, M.D., associate professor, Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University. “We are excited to partner with Viz.ai and pioneer investigator-initiated research that will reveal the impact of AI technology in revolutionizing patient care.”

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