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Corin commenced a significant update to the CorinRegistry™ data warehouse. Corin’s clinical data science and analytics platform, operating within their cloud-based CorinConnect™ digital ecosystem, aims to build knowledge and predictive outcome models from longitudinal care data and Corin’s differentiated patient-specific technologies, enabling surgeons to tailor treatment to each individual patient.
This update to the CorinRegistry combined 150,000 de-identified and annotated radiographic hip and knee images, collected over the years through Corin’s services, into the secure database, and created a pipeline for all future imaging data to be automatically deidentified and ported into the CorinRegistry. This data will be used to further research patient biomechanics for consideration of optimal treatment pathways.
For example, Corin’s OPSInsight™ pre-operative planning for total hip arthroplasty (THA) may benefit from key landmarking of patient imaging, identifying potential risk factors and the need for further examination.
“These data and images create a foundation of training datasets for our machine learning, AI and computer vision initiatives. By combining our annotated images with our data science capabilities, we are developing tools that can auto-identify THA patients who are at risk for adverse spinopelvic mobility and related complications such as prosthetic dislocation, using only one or two routine x-ray images. This will enable surgeons and hospitals to markedly streamline clinical care pathways and deliver more cost-effective and time-efficient treatment. It has the potential to reduce complications and improve care on a much wider scale,” said Jim Pierrepont, Corin’s Global Franchise Lead for Technology.
Christopher Plaskos, Corin’s Global VP of Clinical Innovation, said, “We are now employing sophisticated AI algorithms in our technology stack to take what we’ve learned from 3D imaging, dynamic modeling and functional radiography, and reduce the amount of imaging required to treat patients undergoing arthroplasty procedures.”
The CorinConnect digital ecosystem is designed to create additional value for orthopedic providers by collecting, collating and displaying data that is generated with every use of Corin technology. As the collection of data grows, the goal is to better understand the factors of total joint arthroplasty that influence outcomes, helping improve procedural technologies and patient-specific care pathways.
Source: Corin Group
Corin commenced a significant update to the CorinRegistry™ data warehouse. Corin’s clinical data science and analytics platform, operating within their cloud-based CorinConnect™ digital ecosystem, aims to build knowledge and predictive outcome models from longitudinal care data and Corin’s differentiated patient-specific technologies,...
Corin commenced a significant update to the CorinRegistry™ data warehouse. Corin’s clinical data science and analytics platform, operating within their cloud-based CorinConnect™ digital ecosystem, aims to build knowledge and predictive outcome models from longitudinal care data and Corin’s differentiated patient-specific technologies, enabling surgeons to tailor treatment to each individual patient.
This update to the CorinRegistry combined 150,000 de-identified and annotated radiographic hip and knee images, collected over the years through Corin’s services, into the secure database, and created a pipeline for all future imaging data to be automatically deidentified and ported into the CorinRegistry. This data will be used to further research patient biomechanics for consideration of optimal treatment pathways.
For example, Corin’s OPSInsight™ pre-operative planning for total hip arthroplasty (THA) may benefit from key landmarking of patient imaging, identifying potential risk factors and the need for further examination.
“These data and images create a foundation of training datasets for our machine learning, AI and computer vision initiatives. By combining our annotated images with our data science capabilities, we are developing tools that can auto-identify THA patients who are at risk for adverse spinopelvic mobility and related complications such as prosthetic dislocation, using only one or two routine x-ray images. This will enable surgeons and hospitals to markedly streamline clinical care pathways and deliver more cost-effective and time-efficient treatment. It has the potential to reduce complications and improve care on a much wider scale,” said Jim Pierrepont, Corin’s Global Franchise Lead for Technology.
Christopher Plaskos, Corin’s Global VP of Clinical Innovation, said, “We are now employing sophisticated AI algorithms in our technology stack to take what we’ve learned from 3D imaging, dynamic modeling and functional radiography, and reduce the amount of imaging required to treat patients undergoing arthroplasty procedures.”
The CorinConnect digital ecosystem is designed to create additional value for orthopedic providers by collecting, collating and displaying data that is generated with every use of Corin technology. As the collection of data grows, the goal is to better understand the factors of total joint arthroplasty that influence outcomes, helping improve procedural technologies and patient-specific care pathways.
Source: Corin Group
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JV
Julie Vetalice is ORTHOWORLD's Editorial Assistant. She has covered the orthopedic industry for over 20 years, having joined the company in 1999.
