Practical Guide for Deployment of AI Solutions in Clinical Environment: How Did We Do It?
2019-08-14
Practical Guide for Deployment of AI Solutions in Clinical Environment: How Did We Do It?
TEACHING POINTS
Every AI company developing/validating algorithms on different modalities has this question in mind - how to deploy AI algorithms in a radiology department?
Different types of deployment options:
On-cloud
On-prem (CPU-only)
On-prem (CPU + GPU)
How to integrate deployment with the department's PACS/Workstation?
Specific Site wise deployment because of Non Uniform data in same modality's images.
How deploying AI algorithms in docker form will be a wise choice?
IOT Devices like raspberry pi can be used for Image data anonymization in an On-cloud setup.
How can the result of the algorithm be transferred back to PACS/Workstation?
How can the result also be shown in the hospital or radiology centre’s HIS/RIS using HL7 messaging?
What type of Hardware configuration can be used in an On-prem deployment?
How to ensure Patient’s Data privacy?
Unlock the potential of CARPL platform for optimizing radiology workflows
