Vendor source

Reviewed 17 Jun 2026

Completeness Strong (72%)

Sycai Medical

Sycai Medical

SYCAI Medical® is a medical device software, based on artificial intelligence, that assists radiologists in the detection and characterization of radiological findings in the pancreas on CT scans of adult patients. SYCAI Medical integrates with the customer's PACS (Picture Archiving and Communication System), ensuring interoperability within the hospital's workflow.

No papers to support — we monitor for new evidence.

Key Features

  • Detect and flag findings
  • Lesion characterization
  • Track changes over time

General Information

Product name

Sycai Medical

Modality

CT

Main task

Detection

Subspeciality

Abdomen

Disease targeted

Pancreatic incidental lesions

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIb

Verified by Health AI Register

Other certifications

Not specified

Evidence & Research

No research papers or evidence on file yet.

The registry monitors publications for new evidence.

Technical Specifications

Patient population age

Adult

Input

Abdominal (or equivalent) CT, Thoracoabdominal (or equivalent) CT, Abdominopelvic (or equivalent) CT, Pancreatic (or liver) CT, Uro-CT (or equivalent), Abdominal (or equivalent) scanner

Input format

DICOM

Output

Position, volume and major axis measurements, evolution compared to previous CT scan, comparison, synchronized scrolling, graphical overlay, report.

Output format

DICOM Secondary Capture, DICOM-SR

Integration

Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform

Deployment

Cloud-based, Locally on dedicated hardware, Locally virtualized (virtual machine, docker)

Trigger for analysis

Automatically, Right after the image acquisition

Processing time

1 - 10 minutes

Population

It is intended to be used with aldults patients undergoing an abdominal CT imaging test.

Market Presence

On market since

09-2024

Resellers

Not specified

Countries present

2

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of analyses

Source: Vendor | First published: Dec 11, 2025 | Last updated: Jun 17, 2026