Developing tools for pre-market evaluation and post-market surveillance of Medical Imaging AI
Lead Participant:
RAIQC LTD
Abstract
AI tools have shown promise in being able to analyse medical imaging and aid healthcare professionals with their image interpretation speed and accuracy. However, the uptake of these algorithms by healthcare organisations has been slow for several reasons including:
? Lack of independent clinical testing about the accuracy of the algorithms.
? Lack of training of medical staff in the use of the algorithms which leads to a lack of confidence in the use of algorithms.
? Difficulties in integration of the algorithms with existing hospital IT systems so the tools can be tried before purchase.
? Lack of trust in the real-world performance of the tools.
RAIQC Ltd has developed a web-based platform for training of medical staff in image interpretation as well as validation of imaging AI algorithms. Through the project, the company aims to further develop their platform into an end-to-end solution for training, testing and deploying AI algorithms that will:
? Allow AI developers to perform _in silico_ clinical trials to generate evidence around the efficacy, usability and health economic value of their AI tools.
? Train medical staff in the safe and appropriate use of AI in medical image interpretation
? Make it easier for hospitals to trial algorithms without the requirement of full integration with the existing hospital systems.
? Monitor the real-world performance of AI tools after they have been deployed in the clinical environments including their accuracy in different diseases, patient demographics and scanner types.
During Phase I of the project, a consortium of AI developers, NHS Trusts, clinicians and academics was put together which will work together to define the technical and clinical requirements of the platform. RAIQC Ltd will then lead the development of the pre-market evaluation and post market surveillance tools and connect them with the hospital IT systems. Once the tools have been developed, they will be used to test algorithms from AI vendors that are part of the consortium. and build
AI has the potential of revolutionising healthcare delivery in the NHS and worldwide by improving diagnostic accuracy and increasing productivity. The outputs of the project will help develop trust in AI and in turn accelerate their adoption into clinical practice.
? Lack of independent clinical testing about the accuracy of the algorithms.
? Lack of training of medical staff in the use of the algorithms which leads to a lack of confidence in the use of algorithms.
? Difficulties in integration of the algorithms with existing hospital IT systems so the tools can be tried before purchase.
? Lack of trust in the real-world performance of the tools.
RAIQC Ltd has developed a web-based platform for training of medical staff in image interpretation as well as validation of imaging AI algorithms. Through the project, the company aims to further develop their platform into an end-to-end solution for training, testing and deploying AI algorithms that will:
? Allow AI developers to perform _in silico_ clinical trials to generate evidence around the efficacy, usability and health economic value of their AI tools.
? Train medical staff in the safe and appropriate use of AI in medical image interpretation
? Make it easier for hospitals to trial algorithms without the requirement of full integration with the existing hospital systems.
? Monitor the real-world performance of AI tools after they have been deployed in the clinical environments including their accuracy in different diseases, patient demographics and scanner types.
During Phase I of the project, a consortium of AI developers, NHS Trusts, clinicians and academics was put together which will work together to define the technical and clinical requirements of the platform. RAIQC Ltd will then lead the development of the pre-market evaluation and post market surveillance tools and connect them with the hospital IT systems. Once the tools have been developed, they will be used to test algorithms from AI vendors that are part of the consortium. and build
AI has the potential of revolutionising healthcare delivery in the NHS and worldwide by improving diagnostic accuracy and increasing productivity. The outputs of the project will help develop trust in AI and in turn accelerate their adoption into clinical practice.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
Participant |
||
| RAIQC LTD |
People |
ORCID iD |
| Mark Beggs (Project Manager) |