Christian Wiedemeyer
Chief Medical Officer
Floy
Floy® develops certified artificial intelligence to assist radiologists in identifying hard-to-detect abnormalities in medical imaging. This technology aims to enhance diagnostic accuracy and reduce the risk of misdiagnosis in conditions such as cancer, cardiovascular diseases, and dementia.
- Artificial Intelligence
- Healthcare Technology
- Medical Devices
- Software Only
Updated 23 months ago
Funding
Raised to date
$9.3MRaised 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.
Funding rounds are not available yet.
Founders
Benedikt Schneider
Managing Director
Product
Problem
Radiologists face challenges in detecting subtle abnormalities in medical images, which can lead to delayed or missed diagnoses of critical conditions like cancer, cardiovascular diseases, and dementia. The increasing volume of medical images and the complexity of certain cases can overwhelm clinicians, increasing the risk of human error.
Solution
Floy develops certified artificial intelligence (AI) solutions designed to assist radiologists in identifying hard-to-detect abnormalities within medical images, enhancing diagnostic accuracy and workflow efficiency. The AI algorithms analyze radiological images to highlight potential areas of concern, acting as a second reader and reducing the risk of misdiagnosis. By integrating AI into the diagnostic process, Floy aims to improve patient outcomes through earlier and more accurate detection of diseases. The platform offers a holistic approach by connecting separated medical fields with the patient's medical history.
Target Audience
The primary target audience includes radiologists, hospitals, and diagnostic imaging centers seeking to improve diagnostic accuracy, reduce errors, and enhance workflow efficiency.
Features
- AI-powered analysis of radiological images for various conditions, including cancer, cardiovascular diseases, and dementia
- Algorithms trained to detect subtle anomalies that may be missed by human readers
- Integration with existing radiology workflows and Picture Archiving and Communication Systems (PACS)
- Support for multiple imaging modalities, such as MRI, CT, and X-ray
- Web dashboard for clinicians featuring visualizations and customizable alert thresholds
- Certified as a medical device