We integrate data from various sources, such as electronic health records (EHRs) and medical devices, to provide a full picture of patient information. Our team cleans and standardizes the data, ensuring it aligns with models like OMOP CDM for compatibility with research standards and more efficient analysis.
Our team specializes in optimizing data extraction, transformation, and loading to improve performance. We help healthcare organizations manage data workflows efficiently, providing insights into patient care, operations, and financial performance.
We create custom ontologies to improve patient history records, apply medical guidelines, and ensure smooth data integration. As part of the OHDSI community, we’ve developed multiple ontologies for various healthcare domains, including disease classification, treatment protocols, and clinical outcomes.
Our team, made up of medical doctors and engineers, specializes in accurately segmenting and labeling anatomical structures in medical images like MRIs and CT scans. With years of experience, we ensure your data is prepared quickly and precisely for analysis.
Our team of experts develops computer vision (CV) algorithms for medical image processing and recognition, as well as natural language processing (NLP) models for handling medical records and claims. Whether you need model training, fine-tuning, or a complete solution, we customize everything to meet your specific needs.
We conduct research within the OMOP CDM ecosystem, handling data mapping, cohort definition, and population analysis. Our team supports every stage, from design to final analysis, turning raw data into publishable research with continuous improvements.
Our team has extensive experience with healthcare data, from converting and mapping data to producing evidence. We offer full support throughout the research process, helping with study design, making improvements, and overseeing every stage to ensure accurate results.
