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In this business case, our customer was a UK-based startup focused on AI and ML tools for processing DICOM images (MRI, CT, X-ray, and PET) and non-imaging data. It provides R&D professionals across life science, academic, and other organizations with advanced cloud-based data analytics tools.
The customer's goal is to provide R&D professionals across life science, academic, and other organizations with advanced cloud-based data analytics tools integrated with various imaging modalities and data sources (PACS, EHR, etc.). The solution we worked on is used for early diagnosing neurological disorders, such as Alzheimer’s disease and multiple sclerosis, as well as for predicting the velocity of memory and cognitive deterioration. The platform leverages AI-enabled multi-modal analysis of data acquired from different sources: medical scans, EHRs, wearable devices, genomic repositories, and more. Andersen assisted the startup team with Front-end and Back-end development to roll out an MVP with a user-friendly interface, integrated with a sophisticated AI-rich back-end part. With this solution, scientists from all over the world can now upload DICOM scans of brain tissue alongside non-imaging data for further processing with unique AI/ML algorithms, effectively identifying the earliest signs of some of our society’s most devastating diseases.
QA manual, DevOps, UX/UI, PM, BA
Andersen's team has contributed to the development of an AI-focused, scalable, and customized clinical decision support platform aimed at diagnosing and predicting progressive degenerative brain diseases. The solution uses multi-modal (MRI, PET, CT, X-ray) imaging and non-imaging data.
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