Ai Metrics, LLC
AI Metrics is a radiology software company founded by Dr. Andrew Smith, MD, PhD, with a mission to help radiologists deliver faster, more accurate evaluations of cancer patients through AI-enabled solutions. The company focuses on improving workflows, reporting, and diagnostic accuracy in radiology, particularly in cancer imaging, to reduce radiologist burnout and enhance patient care.
Industries
Nr. of Employees
small (1-50)
Ai Metrics, LLC
Products
Cancer imaging analysis software platform
A cloud-capable imaging analysis platform for advanced cancer reads that combines guided workflows, automated tumor detection/measurement, longitudinal response analytics (RECIST), and automated visual reports to accelerate and standardize oncology imaging interpretation.
CT-derived liver surface nodularity biomarker module
A CT-based digital biomarker implementation that quantifies liver surface nodularity to aid staging of liver fibrosis and prediction of liver-related events from routine CT exams.
Cancer imaging analysis software platform
A cloud-capable imaging analysis platform for advanced cancer reads that combines guided workflows, automated tumor detection/measurement, longitudinal response analytics (RECIST), and automated visual reports to accelerate and standardize oncology imaging interpretation.
CT-derived liver surface nodularity biomarker module
A CT-based digital biomarker implementation that quantifies liver surface nodularity to aid staging of liver fibrosis and prediction of liver-related events from routine CT exams.
Services
Clinical software implementation and IT integration
Secure cloud deployment and technical integration with existing PACS, RIS, and EMR systems; supports Active Directory authentication and contextual image display on existing viewers. Includes collaboration with site IT teams to enable installation and integration.
Clinical validation and research collaboration
Partnerships and participation in multi-institutional comparative-effectiveness studies and clinical research to validate performance metrics such as read time, accuracy, error reduction, and inter-observer agreement.
Automated reporting and workflow training
Implementation of automated visualized reporting into clinical workflows and training for radiologists on guided review processes that reduce manual reporting burden and standardize outputs for oncologists.
Clinical software implementation and IT integration
Secure cloud deployment and technical integration with existing PACS, RIS, and EMR systems; supports Active Directory authentication and contextual image display on existing viewers. Includes collaboration with site IT teams to enable installation and integration.
Clinical validation and research collaboration
Partnerships and participation in multi-institutional comparative-effectiveness studies and clinical research to validate performance metrics such as read time, accuracy, error reduction, and inter-observer agreement.
Automated reporting and workflow training
Implementation of automated visualized reporting into clinical workflows and training for radiologists on guided review processes that reduce manual reporting burden and standardize outputs for oncologists.
Expertise Areas
- Oncologic imaging workflow automation
- Clinical validation and comparative-effectiveness studies
- Digital biomarker development for CT
- Medical imaging AI model development
Key Technologies
- Deep learning for medical imaging
- Automated lesion detection and measurement
- Longitudinal imaging analytics
- RECIST 1.1 computational implementation