RNT Health Insights develops AI-assisted Software as a Medical Device (SaMD) that enhances real-time detection of upper gastrointestinal lesions, including early gastric cancer, during endoscopic procedures. By utilizing advanced algorithms to analyze endoscopic imaging, the solution improves diagnostic accuracy and reduces the likelihood of missed diagnoses, ultimately facilitating timely patient intervention.
Funding
$30K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Endoscopists face challenges in detecting subtle upper gastrointestinal lesions, including early gastric cancer, during routine endoscopic procedures, potentially leading to missed or delayed diagnoses. The subjective nature of visual inspection and the variability in endoscopist experience can impact diagnostic accuracy.
Solution
RNT Health Insights develops AI-assisted Software as a Medical Device (SaMD) designed to enhance the real-time detection of upper gastrointestinal lesions during endoscopic procedures. By applying advanced computer vision algorithms to analyze endoscopic imaging, the solution provides endoscopists with real-time decision support, highlighting suspicious areas that may warrant further investigation. The technology aims to improve diagnostic precision, reduce the rate of missed diagnoses, and facilitate timely intervention for patients with early-stage gastrointestinal cancers. The solution has received FDA Breakthrough Device Designation for its potential to improve early diagnosis and treatment of gastrointestinal lesions.
Target Audience
The primary target audience includes gastroenterologists, endoscopists, and hospitals seeking to improve the accuracy and efficiency of upper gastrointestinal lesion detection during endoscopic procedures.
Features
- Real-time analysis of endoscopic video feeds using AI-powered computer vision algorithms
- Detection and highlighting of suspicious lesions indicative of early gastric and esophageal cancers
- Integration with existing endoscopy equipment for seamless workflow implementation
- Structured data annotation for continuous improvement of AI model accuracy
- Analytics dashboard providing diagnostic and prognostic insights