Lunit Cancer Screening
Lunit develops AI-powered medical imaging solutions that enhance early-stage cancer detection and predict treatment responses for immunotherapy. By leveraging advanced algorithms, Lunit's technology increases the accuracy of cancer screenings and improves patient outcomes across over 3,800 healthcare sites in more than 50 countries.
- Artificial Intelligence
- Data & Analytics
- Digital Health
- Healthcare Technology
- Software Only
Funding
Raised to date
$135.1MRaised 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.
across 7 rounds
+8$61M · Post-Ipo
Announced Nov 2021
Disclosed cumulative: $135.1M
Founders
Product
Problem
The accuracy of cancer screenings and prediction of treatment responses remain significant challenges in healthcare, impacting early detection and treatment efficacy. Traditional methods often lack the precision needed for timely intervention and personalized treatment plans.
Solution
Lunit offers AI-powered solutions designed to enhance cancer detection and treatment prediction through advanced medical image analysis. Their technology leverages deep learning algorithms to improve the accuracy of cancer screenings, enabling earlier and more reliable diagnoses. Additionally, Lunit's AI predicts treatment responses, particularly for immunotherapy, allowing for more effective and personalized treatment strategies. By integrating AI into clinical workflows, Lunit aims to improve patient outcomes and provide comprehensive cancer care.
Target Audience
Lunit's primary audience includes healthcare providers, hospitals, and research institutions focused on oncology, radiology, and immunotherapy.
Features
- AI-driven analysis of medical images for early cancer detection
- Predictive AI biomarkers to forecast immunotherapy treatment response
- Integration with existing healthcare systems and workflows
- Access to a vast library of research with over 200 studies and abstracts
- Algorithms trained on diverse datasets to ensure broad applicability