WSK Medical has developed Zeno AI, a real-time automated solution for the detection and classification of laryngeal benign lesions and carcinomas during endoscopic examinations. This technology enables clinical specialists to identify throat cancer at an early stage, improving diagnostic accuracy and patient outcomes.
Funding
$330K 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
Early detection and accurate classification of laryngeal and oral cavity cancers during endoscopic examinations are critical for improving patient outcomes, but current methods often rely on subjective visual assessments. This can lead to delayed diagnoses, unnecessary referrals, and variability in treatment decisions.
Solution
WSK Medical's Zeno AI is an AI-powered software solution designed to assist clinical specialists in the real-time detection and classification of benign lesions and carcinomas in the larynx and oral cavity during endoscopic procedures. By analyzing endoscopic images, Zeno AI provides immediate feedback on potential lesion location and type, aiding in early diagnosis and differentiation between benign, premalignant, and malignant oral lesions. The AI algorithms are trained to capture the specialized knowledge of head and neck oncologists, making it accessible to ENT and dental clinicians. The goal is to enhance diagnostic accuracy, reduce workload, and improve patient care through earlier, more precise diagnoses and treatment.
Target Audience
The primary target audience includes ENT (Ear, Nose, and Throat) specialists, head and neck oncologists, dental professionals, and general practitioners involved in the diagnosis and treatment of laryngeal and oral cavity cancers.
Features
- Real-time analysis of endoscopic video during laryngoscopic and oral cavity examinations
- AI-driven detection and classification of laryngeal and oral cavity lesions
- Identification of potential benign and malignant lesions
- Integration of AI algorithms trained on expert knowledge of head and neck oncology
- Support for early diagnosis and differentiation between lesion types
- Streamlined workflow for ENT and dental clinicians
- Potential for integration into telemedicine practices for remote evaluation