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Data Ingestion for AI in Prostate Cancer
Haridimos Kondylakis1, Stelios Sfakianakis1, Varvara Kalokyri1
1FORTH-ICS, N Plastira 100, Heraklion, Crete, Greece.
Studies in Health Technology and Informatics
|May 25, 2022
Summary
Prostate cancer diagnosis can be improved with artificial intelligence. The ProCAncer-I project is building a platform to integrate prostate cancer imaging data for better diagnostic tools.
Area of Science:
- Oncology
- Medical Imaging
- Artificial Intelligence
Background:
- Prostate cancer (PCa) is a leading cancer in men.
- Current diagnostic methods risk overdiagnosis and overtreatment.
- Improved diagnostic tools are needed to enhance patient quality of life.
Purpose of the Study:
- To present the architecture of the ProCAncer-I AI platform.
- To focus on the data ingestion aspects of the platform.
- To describe the data storage and workflow for PCa imaging and clinical data.
Main Methods:
- Developing an AI platform integrating imaging data and models.
- Creating the largest global collection of prostate cancer (mp)MRI data.
- Implementing a data ingestion workflow for uploading and storing anonymized data.
Main Results:
- An overview of the ProCAncer-I platform architecture is presented.
- The data ingestion workflow for PCa imaging and clinical data is described.
- Repositories for storing imaging data, clinical data, and metadata are established.
Conclusions:
- The ProCAncer-I project is establishing a significant resource for AI-driven PCa research.
- The platform aims to improve prostate cancer diagnosis through integrated data and AI models.
- Effective data management is crucial for building a comprehensive PCa database.
