AI in healthcare diagnostics: Scaling a patient data platform project
5 days
to onboard new specialists
95%
retention rate
31%
fewer diagnostic errors
IT-service type
IT-staff augmentation
Business vertical
MedTech / Healthcare AI
Cooperation period
July 2023 – ongoing
Dedicated team size
6 IT specialists*
* Peak team size at the time of case study publication
Partner
A reputable German medtech provider specializing in oncology diagnostics and personalized patient care.
Partner’s challenges
Limited internal AI expertise to expand the clinic’s patient data management system.
Requirement to ensure full compliance with European healthcare data protection standards.
Need for experienced specialists in integrating predictive analytics in oncology into clinical workflows.
Lack of resources to maintain quality assurance and continuous testing for AI diagnostic tools in healthcare.
Process of selecting required IT-specialists
Specialist selection (1 day)
Modsen shortlisted AI engineers and QA experts with proven healthcare and compliance background.
Technical interview (3 days)
Assessment of technical expertise in AI for healthcare diagnostics, Java, and AWS.
Final interview (2 days)
Evaluation of teamwork approach and alignment with the client’s working culture.
Security check (5 days)
GDPR compliance and background verification under German healthcare standards.
Project start (within 5 days)
Modsen experts integrated with the client’s IT department following verified onboarding and data-protection protocols.
Scale your healthcare AI projects with vetted engineers ready to join in days.
Engagement timeline
*Demonstrative team dynamics from project launch to the time of case study publication.
Feature development by Modsen IT-specialists
Development of AI algorithms for diagnostic accuracy and treatment recommendations
Integration of predictive analytics in oncology into the platform’s core logic
Creation of patient data management and visualization modules
Implementation of secure API connections with hospital databases and EHR systems
Design of automated data validation and anomaly detection features
Continuous QA testing of AI diagnostic tools in healthcare
Performance tuning of AWS-based components and data pipelines
Dedicated team size | 6 IT-specialists |
Delivered expertise | Java, React, AWS, PostgreSQL, AI, QA. |
Development methodology | Hybrid model: Agile delivery within Modsen’s AI unit aligned with the clinic’s regulated validation and approval process. |
Retention rate | ~95% throughout the partnership. |
Average hiring cycle | Up to 16 days from request to full team onboarding. |
Strategic business value |
|
We’re ready to share more results from our AI in healthcare projects and discuss how we can support yours.