Diagnostic Pathway Management and Data Enrichment
Gain a deep understanding of your diagnostic data sets and enrich them for higher quality diagnostic algorithms
Simplified feature engineering
Use our mapping tools and quickly evaluate, whether your medical datasets can fulfill the needs for diagnostic analytics – in terms of completeness and complexity. Uncover potential biases e.g. related to gender or age.
Data Labeling
and Enrichment
Gain an understanding of potential diagnosis within your dataset and check for errors and potential diagnostic optimization. Enrich your dataset based on our GMP-based algorithms – especially in the area of laboratory diagnostics.
Diagnostic Pathway optimization
Leverage historic, clinical datasets to uncover areas for improvement in diagnostic procedures. Discover medical sub-groups and explore risk factors. Combine medical and economical datasets for optimal healthcare outcomes and efficient diagnostic pathway management.
Research
Clinical Trials and Medical Research
Leverage the medicalvalues platform to become more agile and data-driven in your clinical data collection and research activities.
Plan your research
Quickly research relevant symptoms, parameters and potential side-effects to plan your study effectively.
Harmonization of findings
Ensure your data points follow a standardized interpretation to ensure comparability.
Real-time preliminary analysis
Get an AI-generated, initial diagnostic recommendation to quickly process large data volumes.
Diagnostic Analytics
Diagnostic Pathway Management and Analytics
Pre-built diagnostic pathway templates enable you to get results from day one. Use our pathways as a solid base and customize them for your individual projects.
Analyze historic data sets
Understand patterns and uncover potential areas for diagnostic savings without compromising on quality.
Run what-if scenarios
GMP Comparison
Compare your diagnostic steps to good medical practice and latest research to analyze potential differences and uncover areas for improvement.
Knowledge Management
Structure and visualize your diagnostic pathways and get a headstart with templates from the medicalvalues library.
Data Intelligence
Machine Learning and Artificial Intelligence
Re-use pre-built integrations into clinical and laboratory systems leveraging standard interfaces like FHIR to integrate your ML-landscape more efficiently.
Data Mapping and Harmonization
Leverage our platform tools to harmonize your datasets and map them to international standards like SNOMED CT and LOINC.
Data cleaning and feature engineering
Quickly identify errors in your datasets and get an understanding of potential bias.
Data enrichment and algorithmic performance
Leverage our pre-built algorithms to (pre-) label your data or compare your algorithms against the GMP-based results.
Start Today
Get started on the medicalvalues platform in 10 minutes
- Map & Normalize your datasets to leading international standards like SNOMED CT and LOINC
- Analyze & Enrich your data with diagnostics insights to kickstart or improve your AI applications and research
- Derive actionable insights in seconds and leverage our diagnostic algorithms to support your medical team or create your own solutions
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.
