| Ticker | Status | Jurisdiction | Filing Date | CP Start | CP End | CP Loss | Deadline |
|---|
| Ticker | Case Name | Status | CP Start | CP End | Deadline | Settlement Amt |
|---|
| Ticker | Name | Date | Analyst Firm | Up/Down | Target ($) | Rating Change | Rating Current |
|---|
Results highlight the role of artificial intelligence development in enabling earlier detection of aortic stenosis.
The Company announces new Aorta Exam training protocol released on Butterfly ScanLab™
Butterfly Network, Inc. (NYSE:BFLY), a digital health company transforming care with handheld, whole-body ultrasound and intuitive software, today announced its role in new research demonstrating the potential for machine learning (ML) models to support early detection of aortic stenosis (AS) using handheld ultrasound devices. The study, conducted by Tufts Medical Center and published in European Heart Journal – Imaging Methods and Practice, demonstrates that a ML model fine-tuned for use on Butterfly iQ+ devices can achieve high accuracy in identifying AS. The findings support the value of ML model development, and ultimately, are a positive step toward portable screening for earlier detection of this life-threatening condition.
Posted In: BFLY
