Integrating NLST Data with InferRead CT Lung AI for Collaborative Learning on Collective Minds Radiology Platform
Principal Investigator
Name
Swati Vara
Degrees
MB BCh BAO
Institution
Infervision UK LTD
Position Title
Medical advisor
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1174
Initial CDAS Request Approval
Jan 2, 2024
Title
Integrating NLST Data with InferRead CT Lung AI for Collaborative Learning on Collective Minds Radiology Platform
Summary
This project aims to transform collaborative learning in lung diagnostics by integrating NLST CT data with AI software findings, onto the Collective Minds Radiology website. The Collective Minds Radiology platform serves as a hub for collaborative endeavours, uniting partners and customers to access a comprehensive array of products and services spanning imaging research, clinical consultations, and radiology education. Users require verification prior to access to cases on Collective Minds. All cases are pseudonymised prior to upload.
At the centre of this initiative lies Infervision's InferRead CT Lung AI Software. This AI technology is designed to analyse CT lung scans, providing automated insights that facilitate the detection and classification of pulmonary nodules with accuracy. InferRead CT lung aims to empower healthcare professionals with comprehensive and timely diagnostic information.
The integration process involves strategically sharing specific CT lung scans, accompanied by AI-driven findings generated through Infervision's InferRead software, onto the Collective Minds Radiology website. This collaborative platform harnesses the power of AI, enabling healthcare professionals to engage in interactive discussions and knowledge exchange. By leveraging the Collective Minds platform and integrating with InferRead CT lung AI, healthcare professionals gain access to an environment tailored for interactive learning and collaboration. This facilitates the exchange of insights, collective expertise, and diverse perspectives on intricate cases, enriching the collective knowledge base. This collaborative exchange aims to enhance diagnostic accuracy by providing professionals with AI-driven insights to augment their expertise, contributing to a culture of continual improvement within the field of radiology.
Through this integration, healthcare professionals can engage in discussions cantered on challenging cases, critically evaluating AI-derived findings alongside their own expertise.
Overall, the project utilises NLST CT data with AI software integration to be shared on the Collective Minds platform, fostering an interactive educational ecosystem that leverages advanced AI capabilities and collective expertise for enhanced patient care and improved diagnostic outcomes.
At the centre of this initiative lies Infervision's InferRead CT Lung AI Software. This AI technology is designed to analyse CT lung scans, providing automated insights that facilitate the detection and classification of pulmonary nodules with accuracy. InferRead CT lung aims to empower healthcare professionals with comprehensive and timely diagnostic information.
The integration process involves strategically sharing specific CT lung scans, accompanied by AI-driven findings generated through Infervision's InferRead software, onto the Collective Minds Radiology website. This collaborative platform harnesses the power of AI, enabling healthcare professionals to engage in interactive discussions and knowledge exchange. By leveraging the Collective Minds platform and integrating with InferRead CT lung AI, healthcare professionals gain access to an environment tailored for interactive learning and collaboration. This facilitates the exchange of insights, collective expertise, and diverse perspectives on intricate cases, enriching the collective knowledge base. This collaborative exchange aims to enhance diagnostic accuracy by providing professionals with AI-driven insights to augment their expertise, contributing to a culture of continual improvement within the field of radiology.
Through this integration, healthcare professionals can engage in discussions cantered on challenging cases, critically evaluating AI-derived findings alongside their own expertise.
Overall, the project utilises NLST CT data with AI software integration to be shared on the Collective Minds platform, fostering an interactive educational ecosystem that leverages advanced AI capabilities and collective expertise for enhanced patient care and improved diagnostic outcomes.
Aims
-Leverage NLST CT data with AI software to detect and classify pulmonary nodules and share these on an online platform for engagement and collaborative learning.
-Encourage healthcare professionals to engage in discussions, leveraging the AI insights to foster collaborative learning and critical analysis.
-Encourage discussions centered on challenging cases, combining AI-driven insights with human expertise to enhance educational value.
-Empower healthcare professionals to utilize AI-generated insights as educational tools, enhancing their diagnostic expertise and approaches.
Collaborators
Infervision
Collective Minds Radiology