medicalvalues platform
Make sense of your data facilitating diagnostic knowledge in a seamless integrated approach
Foundation
Core Components
The medicalvalues platform offers various core components
working together to create an integrated foundation for your use cases.
Diagnostic template pathways from various medical areas including: Endocrinology, Infectiology, Hemostaseology, Oncology, Rheumatology, Nephrology, and many more.
Usable as templates for e.g. data mapping, diagnostic data enrichment and other applications on the medicalvalues platform.
Validated and reviewed by leading experts (Learn more).
Facilitates diagnostic template content to bring intelligence to existing data sets.
Advanced rule-based algorithms to process large datasets from a diagnostic perspective. Our white-box AI enables explainable outputs.
Customizable with e.g. your laboratory reference ranges or custom medical content created with the Diagnostic Pathway Editor. View analysis results for output in an integrated way.
Various AI modules to process input data directly from integrations.
Built-in hybrid AI algorithms to combine existing knowledge from medical template content and your own datasets.
Pre-defined healthcare data cleaning and analysis methods.
Interfaces for common standards: FHIR, HL7v2, REST, JSON, XML.
Standard integrations to various laboratory information systems (LIS / LIMS). Connect your system and be productive from day one.
Automatically pre-process and analyze incoming data facilitating medical content and standards.
Combine and store your medical data in a safe and high-performance environment.
Optimized for the needs and structure of medical data. No lock-in through standard formats and open APIs (HL7v2 / FHIR).
Intelligent data management with different data groups (e.g. retention policies and customizable data-flows).
The use of the Medical Data Store is optional. Existing infrastructure or on-demand processing can be applied.
Tools
Available Platform Tools
The medicalvalues platform offers several pre-build tools to kickstart your data-driven use cases.
Map
Diagnostic Data Mapper
Automated data mapping for medical standards like LOINC or SNOMED CT
Easy-to-use step by step process – download your finished mapping or use it directly in the medicalvalues platform
Benefit from latest standard updates which can directly be adapted to your mapping
Enrich
Diagnostic Data Enrichment
Enrich your medical data with validated medical diagnostic knowledge
Identify medical inconsistencies: Detect issues with units, reference range and erroneous diagnoses in your statistical datasets
Add SNOMED CT, LOINC, ICD10, ICD11, Radlex to your data in an integrated way
Knowledge
Diagnostic Pathway Editor
View and edit diagnostic medical template content
Create your own diagnostic pathways as a basis for further use cases
Easy to use drag-and-drop user-interface to explore links and interactions between symptoms, diseases, parameters and more
Optimize
Diagnostic AI Optimizer
Optimize your own and existing template pathways using Artificial Intelligence
Compare existing machine learning models with knowledge graph-based approaches
Speed up machine learning projects through data cleaning, labeling and medical feature engineering
Blog Articles & News
Next Generation Ordering System: The evolution of laboratory ordes and report view in three generations
Laboratories have long recognized the benefits of digital communication with their customers. Printed test catalogs and paper-based order forms with color-coded categories are increasingly becoming a thing of the past, gradually being replaced – or at least supplemented – by electronic ordering systems.
Track & Trace – quality improvement for medical pre-analysis
Modern laboratory diagnostics are very precise. Thanks to highly developed measurement technology and numerous control mechanisms (precision controls, interlaboratory tests, accreditation, etc.), serious measurement errors in the laboratory are virtually impossible. Faulty laboratory results are usually not caused by faulty laboratory analysis, but are due to (human) errors in pre-analysis. Sample tracking is a useful tool for minimising errors in the pre-analytical phase and improving the classification of any measurement inaccuracies.
