Technical Advisor: AWS
Amazon Web Services (AWS) is proud to support the CLAIMS project with financial assistance for data hosting and computational resources. AWS will provide CLAIMS with AWS Credits for storage and computing on AWS to power their deep learning models and analysis of medical imaging data.
AWS is also contributing technical guidance on leveraging Amazon SageMaker for CLAIMS’ prognostic modeling and MRI image processing workloads. SageMaker’s capabilities for scalable and distributed training on large healthcare datasets will enable more efficient development of accurate models. SageMaker streamlines the end-to-end ML process from data prep and feature engineering to training, tuning, and deployment while maintaining security and compliance for sensitive data.
By providing financial credits and technical expertise, AWS aims to accelerate CLAIMS’ use of ML for improved clinical decision making. AWS is excited to collaborate with CLAIMS on this impactful research that can enhance outcomes for multiple sclerosis patients.
Ethics Advisor: Wes Damen
With a background in history, philosophy (ethics), and law, Wessel’s work experience combines work as a lawyer, as a researcher, and as an advisor on research ethics. His research focuses on legal and ethical challenges posed by technological innovations in the areas of healthcare, social security, and academic research. He has profound experience as an ethics and data-protection advisor for multiple European research projects and it’s in this capacity that he will support the CLAIMS project.
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AWS |
Amazon Web Services (AWS) is proud to support the CLAIMS project with financial assistance for data hosting and computational resources. AWS will provide CLAIMS with AWS Credits for storage and computing on AWS to power their deep learning models and analysis of medical imaging data. AWS is also contributing technical guidance on leveraging Amazon SageMaker for CLAIMS' prognostic modeling and MRI image processing workloads. SageMaker's capabilities for scalable and distributed training on large healthcare datasets will enable more efficient development of accurate models. SageMaker streamlines the end-to-end ML process from data prep and feature engineering to training, tuning, and deployment while maintaining security and compliance for sensitive data. By providing financial credits and technical expertise, AWS aims to accelerate CLAIMS' use of ML for improved clinical decision making. AWS is excited to collaborate with CLAIMS on this impactful research that can enhance outcomes for multiple sclerosis patients. |
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Wes Damen |
With a background in history, philosophy (ethics), and law, Wes' work experience combines work as a lawyer, as a researcher, and as an advisor on research ethics. His research focuses on legal and ethical challenges posed by technological innovations in the areas of healthcare, social security, and academic research. He has profound experience as an ethics and data-protection advisor for multiple European research projects and it’s in this capacity that he will support the CLAIMS project. |
