Data Science

With Data Science as a service, our clients can experience the power behind data. We frame your problem and guide your through the stages of the data science life cycle to deploy the solution that answers your challenge.

Our interdisciplinary competencies in data security, data management and data science enable us to convert data into knowledge and technology.

Main pillars of our data science life cycle

  • Consulting Data Science/Machine Learning
  • Ingesting data from required sources
  • Preparing data for modelling purposes
  • Identifying appropriate algorithms for specific use cases
  • Developing Machine Learning models
  • Ranking & scoring data
  • Training & retraining models
  • Deploying models as a service
  • Developing problem-specific workflow tools for technical users
  • Analysing federated, GDPR-proof multi-site, private data without data collection or access

Application Areas

Document Processing
  • Document classification
  • Document digitalisation with NLP
  • Unstructured variables extraction from free text
Federated Analysis
  • Collaborative data science without data collection for private data or for sensitive company information across different countries and regions within the same company
  • Data usage for modeling, analysis or reporting without transferring or accessing data
  • Online customer onboarding and face recognition
  • Fraud detection
  • Trading robots
  • Investment and sentiment analysis
  • Customer data management
  • Customer insight generation
  • Risk modelling and prediction
  • Customer lifetime value prediction
  • Customer support and chatbots
  • Recommendation engines
  • Real-time and predictive analysis
Health and Clinical Research
  • Medical image analysis and recommendation
  • Virtual Assistance for specialists or customer support
  • Risk modelling and treatment prediction
  • Treatment personalisation, personal medicine analysis
  • Medical knowledge and clinical variable extraction from clinical reports
  • ECG/wearable data analysis
  • Biomarker discovery
  • Drug repositioning
  • Network analysis
  • Edge/IOT data analysis
  • Network health analysis

Case Studies

Clinical data mining with AI

Extracting oncology-related indicators and laboratory test results from free-text medical records for searchable and more complete patient pathways at hospitals. We are collecting data and markers from medical records, digital fever systems, neurotrauma database, conducting neuromonitoring, neuroimaging, electrophysiology, and patient pathway monitoring.

An ECG analysis success story

With our contribution, complex individual monitoring of relevant sensory data can be used for reliable prediction of seizures while eliminating the risk of invasive treatment. We set up an automated analysis pipeline and a visual clinical research tool for a clinical study for seizure prediction based on data from wearable ECG sensors and continuous recordings.

Drug development, ML second opinion use case

Drug innovation usually takes considerable time and research. With ML, time and cost required can be substantially decreased, and the reliability of the results will be improved. The analysis report provided for drug researchers supports the hypothesis on a target molecule with an intelligent second opinion analysis.

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