The Orion Health Orchestral Research Platform has highly scalable data and machine learning capabilities that empower healthcare organisations to effectively leverage their data and intelligence assets.
A Health Research Platform plays a pivotal role in the healthcare industry by addressing numerous challenges faced by researchers and ultimately enhancing their work. With its intelligent insights and advanced features, it provides researchers with a powerful tool to navigate the complexities of healthcare data and unlock valuable knowledge.
With a comprehensive data source, machine learning capabilities, and privacy protection, researchers can easily navigate and analyse vast amounts of data, uncover hidden patterns, and make informed decisions.Â
With automated coding and future-proof design, the platform streamlines research processes and keeps researchers ahead of emerging technologies. It’s a reliable companion that empowers researchers to make groundbreaking contributions to healthcare.
Enables academic and health organisations to manage, govern and share their data sets, ensuring integrity, privacy, and security throughout the research process.
By leveraging machine learning and natural language processing, the Research Platform empowers organisations to gain valuable insights into population health, enabling more accurate risk modeling and informed decision-making.
Simplifies the management of research models, including model development, training, testing, and version control, allowing for efficient deployment and continuous improvement.
Research networks, universities, and partnerships can securely share de-identified data and collaborate, overcoming challenges related to federated or regionally-separated data environments while ensuring data confidentiality and compliance.
Safely share data by de-identifying and removing personal information, ensuring compliance with global data protection laws and guidelines. All this while retaining valuable data and discovering new insights.
Facilitates data science activities through Jupyter Hub and Jupyter notebooks for data science or Excel for familiar data exploration.
Secure exploration of healthcare data, managing the model lifecycle, and facilitating real-time algorithm execution for timely insights and enhanced decision-making.
Extracts insights from unstructured clinical data, identifying relevant phrases, entities, and relationships.
Stores raw data, HL7 results, reference data, images, and genomic variance files, while promoting collaboration among data scientists through shared training data and models.
Offers centralised storage, monitoring, and execution of algorithms and models, simplifying their lifecycle management and enabling seamless integration with third-party applications via a REST API, including importing pre-built algorithms.
Safely share data by de-identifying and removing personal information, ensuring compliance with global data protection laws and guidelines.
Extracts insights from unstructured clinical data, identifying relevant phrases, entities, and relationships.
Intuitive data visualizations to create insights for:
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