Tissue Analytics provides a platform that utilizes AI and 3D imaging to automate wound measurement and documentation, significantly reducing measurement error to less than 4%. This technology streamlines workflows by saving clinicians 5-10 minutes per patient in documentation time and seamlessly integrates with all major EMR systems.
Funding
Funding not disclosed
Founders
Product
Problem
Clinicians face challenges in accurately and consistently documenting wound measurements using traditional methods, leading to potential errors in treatment plans and hindering effective monitoring of healing progress. Manual wound measurement is time-consuming, prone to human error, and lacks seamless integration with electronic medical records (EMRs).
Solution
Tissue Analytics offers an AI-powered platform that automates wound measurement and documentation using 3D imaging. The platform reduces measurement error to less than 4% compared to the 44% error rate associated with ruler measurements. By streamlining workflows and integrating with major EMR systems, Tissue Analytics saves clinicians 5-10 minutes per patient in documentation time. The platform provides a more complete longitudinal record and tissue composition data, leading to more informed treatment decisions.
Target Audience
The primary target audience includes nurses, clinicians, and administrators in hospitals, wound care centers, and other healthcare facilities who need accurate and efficient wound measurement and documentation tools.
Features
- AI-driven analysis of wound images for automated measurement of length, width, and surface area
- 3D imaging capabilities for detailed assessment of wound characteristics
- Seamless integration with major EMR systems for efficient data transfer and documentation
- Mobile application for image capture and data collection at the point of care
- Secure cloud-based platform for data storage and analysis
- Longitudinal tracking of wound healing progress with visual representations and reports
- Customizable reporting features for individual patient monitoring and population health analysis