Sycai Medical develops an AI-powered radiology assistant that automates the detection and monitoring of pre-cancerous lesions in abdominal CT scans, integrating seamlessly into existing hospital PACS systems. This technology enables radiologists to identify incidental findings and track lesion evolution without manual input, enhancing early cancer detection and improving patient outcomes.
Funding
$4M 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
Radiologists face increasing workloads and time pressures due to a global demand for cancer imaging services, leading to potential diagnostic errors and radiologist burnout. Detecting and monitoring pre-cancerous lesions in abdominal CT scans is a manual and time-consuming process, increasing the risk of late cancer diagnoses.
Solution
Sycai Medical offers an AI-powered radiology assistant that automates the detection, characterization, and monitoring of lesions in abdominal CT scans, focusing initially on the pancreas with planned expansion to the liver and kidneys. The software integrates directly into existing hospital PACS systems, providing zero-click analysis and instant retrieval of prior patient scans for comparison. By automating lesion tracking over time, the platform aims to standardize reporting, reduce diagnostic time, and improve the early detection of potentially cancerous lesions. The AI algorithms are trained with a large dataset of images and validated in clinical settings to ensure high sensitivity and specificity.
Target Audience
The primary target audience includes radiologists and imaging diagnostics departments within hospitals and clinics seeking to improve diagnostic precision, reduce workload, and enhance early cancer detection rates.
Features
- AI-driven detection and characterization of lesions in abdominal CT scans
- Automatic comparison of current and previous scans to track lesion evolution
- Seamless integration into existing hospital PACS systems with DICOM compliance
- Zero-click workflow integration, delivering results without manual activation
- Patented technology for single-lesion tracking over time
- Compliant with ISO 13485, MDR, GDPR, and DICOM standards
- High sensitivity (96.6%) and specificity (84.5%) in lesion detection
- Full abdomen approach enabling expansion to other organs and pathologies