Advanced Data Enrichment Tool for Optimized Maintenance of Medical Imaging Systems

My name is Milosh Stolikj and I work at Philips as Senior Data Scientist.

Philips designs and produces capital-intensive medical imaging systems, such as Magnetic Resonance Imaging, and Computed Tomography, which are used for diagnosis and image-guided therapy in hospitals.

What are the challenges related to enRichMyData project and in particular to its toolbox that you face in your operations?

Over the years the functionality of this equipment has grown dramatically, which makes system design, verification, and especially maintenance harder with every system release. We see that Big Data and AI technologies can help unveil new insights in product use and develop smart diagnostic tools to improve maintenance.

How does the adoption of the enRichMyData toolbox help you address these challenges?

We leverage the enRichMyData toolbox to enrich our unstructured and semi-structured service data semantically. This enables us to interlink different data sources, improving our knowledge base.

Which parts of the toolbox (tools and/or services) are you going to use and for what exactly?

We are using the Platform Document Analysis component, developed by Expert.AI, to enrich our service documentation. It processes and semantically enriches service manuals, troubleshooting guides, and previous service reports. This enables service engineers to quickly access comprehensive and relevant information when diagnosing and repairing equipment. For instance, a service engineer encountering an error with a Magnetic resonance imaging system can quickly access enriched documentation that highlights relevant troubleshooting steps based on past service reports and manuals, thereby speeding up the repair process.

What will be the benefits of the enRichMyData toolbox adoption:  first – for your business area and second –  for the end-users in your business area?

Enhanced documentation allows engineers to perform maintenance more effectively, leading to faster issue resolution and reduced downtime for medical imaging systems. This ensures higher utilization rates and better service for hospitals and patients.

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