AI Safety White Paper
A comprehensive strategy for ensuring AI safety from pre- to post-deployment. Download
Build Your Radiology AI Solution Seamlessly on deepcOS
Bridge the gap between AI research and clinical application on one comprehensive platform.
From Research to Production
With its Build functionality, deepcOS® is optimized to support the entire AI development process from research to production. Whether you're a medical researcher looking to validate and deploy your AI model in your clinical environment or an AI vendor aiming to quickly expand your market reach, the enterprise-grade deepcOS® offers a robust, integrated platform that automates data handling, streamlines validation, and ensures reliable deployment. This allows you to overcome complex engineering challenges and focus on achieving faster, more reliable results for your AI model’s performance.
Streamlined Validation of Your AI Models
In-house AI models need additional data to assess their real-world performance. deepcOS® enables comprehensive validation in your clinical setting.
Automated Data Handling deepcOS® eliminates the need for manual data extraction and preparation by automating these processes within the clinical workflow.
Integrated Environment AI models can be validated directly in a production-like environment without setting up additional infrastructure.
Comprehensive Evaluation Gather assessments of model performance, user experience, and clinical outcomes, providing robust evidence for journal publication and commercialization.
Efficient Deployment of Your AI Models
Setting up your own DICOM server demands extensive time and expertise, diverting focus from your core AI research and innovation. Leverage an established infrastructure to significantly streamline deployment and enhance productivity.
Infrastructure Support deepcOS®’ scalable and secure infrastructure removes the need to build and maintain bespoke systems.
Seamless Integration Smooth deployment and operation of in-house AI models, integrating with existing clinical workflows.
Flexibility Cloud and on-premises deployment options to suit development needs, security requirements, and infrastructure preferences.
Self-service integration of your AI models in real-time
Move your AI model from development to clinical practice without challenges from backend engineering and IT prioritizations.
Compatibility with MONAI MAPs
MONAI framework allows developers to rapidly prototype, train, and deploy AI models for medical imaging applications. With MONAI MAPs containers, AI models are seamlessly delivered via deepcOSⓇ’ Build workflow.
Transparency in integration
See all of your submissions at a glance and access tooling to troubleshoot submissions in real-time
Insights into your AI solution’s performance
Comprehensive dashboard enables users to monitor submitted AI solutions, gaining insights into execution time, success rate, and JSON-related metrics.
Looking to deploy your research AI engine?
Resources
deepc joins King’s Health Partners Digital Health Hub
deepc will share its expertise with AI-focused medtech startups, helping them scale quickly and avoid first-time regulatory and technical pitfalls.
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Cloud or On-Prem?
Navigating AI deployment includes determining the best setup for your clinical organization. See what factors are involved in choosing between a cloud and on-prem platform.
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