AI-Powered Diagnostic Precision

Our AI algorithms have received FDA 510(k) clearance for specific diagnostic imaging applications. The platform is designed as a diagnostic aid to augment radiologist capabilities, not as a standalone diagnostic tool. Final diagnosis must always be made by qualified healthcare professionals. We provide documentation of our regulatory status for each specific use case.

AI Medical Imaging integrates seamlessly with major PACS systems including GE, Philips, Siemens, Agfa, and others through standard DICOM protocols. The integration is non-disruptive - images are automatically processed in the background as they arrive in your PACS. Typical deployment takes 2-4 weeks with minimal IT involvement required.

Absolutely not. AI Medical Imaging is designed to augment radiologists, serving as an intelligent second opinion that helps detect subtle findings, prioritize critical cases, and reduce turnaround time. The AI handles the heavy lifting of initial screening, allowing radiologists to focus their expertise on complex cases and final interpretation. All findings require radiologist review and confirmation.

Our AI achieves sensitivity rates up to 99% and specificity up to 97% depending on the imaging modality and clinical condition. These results have been validated through clinical studies with major academic medical centers. We provide detailed accuracy metrics and clinical study data for each specific use case upon request.

Patient data security is our highest priority. We are fully HIPAA compliant and hold SOC 2 Type II certification. All data is encrypted end-to-end using AES-256 encryption. We offer flexible deployment options including on-premise installation for organizations that require data to remain within their facilities. Patient data is never used for model training without explicit consent.

We support a comprehensive range of imaging modalities including: X-rays (chest, skeletal, dental, mammography), MRI (brain, spine, musculoskeletal, cardiac), CT scans (head, chest, abdomen, whole-body), digital pathology/histopathology, and ultrasound (obstetric, cardiac, abdominal, vascular). Each modality has specific AI models optimized for that imaging type.

Yes, AI Medical Imaging is particularly effective for population screening programs where it can help process high volumes of studies efficiently. The AI can pre-screen studies and flag potential abnormalities for radiologist review, significantly improving throughput while maintaining diagnostic accuracy. We have experience deploying for lung cancer screening, mammography screening, and other population health initiatives.

Implementation typically follows four phases: (1) Technical assessment and integration planning (1 week), (2) PACS integration and system configuration (1-2 weeks), (3) Validation testing with your studies (1 week), and (4) Go-live with ongoing support. Our team handles most of the technical work, requiring minimal involvement from your IT and radiology staff. We provide comprehensive training for all users.