Case studies

We have extensive experience in automating mappings between medical coding and classification systems by computationally processing their semantic meaning, which can be extracted using NLP methodology or explicitly available from the classification model. Our successful applications include mappings made from ICD-10-PCS, LOINC, and ICD-O-3 systems for OHDSI OMOP Standardized Vocabularies.

The client is a healthcare company focused on medical imaging and diagnostics, working to improve the diagnosis of lung diseases like tuberculosis and COVID-19. They wanted to create an AI-based algorithm that could detect abnormal changes in chest X-rays and automatically prioritize the most urgent cases. It helps to make the diagnostic process faster and more accurate by identifying abnormalities and highlighting critical cases. It reduces the workload for radiologists and pulmonologists by automating routine tasks, so they can focus on more complex cases. By solving issues like delayed diagnoses and heavy workloads, the solution ensures patients with serious conditions get quicker and more reliable care.

Our client in the corporate EdTech sector developed a platform that aggregates business courses for easy access and management. They sought an automated system to categorize courses into areas like marketing, finance, and HR, and to recommend personalized learning paths based on each employee's role and career goals. Read on to learn about our ML solution that transforms course categorization and tailors personalized recommendations.

Our solution uses advanced Natural Language Processing (NLP) and Machine Learning (ML) to automate the extraction of detailed specifications and measurements from complex product spec sheets.

Transform your legal document management with our advanced AI system. Built to streamline contract analysis, this solution cuts down on manual work and boosts accuracy, making the process of handling legal contracts more efficient and precise.

Our product brings a new healthcare claims management approach with AI-driven capabilities. It streamlines claim processing and reduces denials, improving efficiency and financial outcomes for healthcare providers.

We designed an ML-powered system for personified lab test results. It boosts the efficiency of physician office laboratories (POLs) and increases the speed of the medical service delivery system. Moreover, the system that we created became a part of a broader telemedical patient care delivery system. Read on to find out how we deal with challenges like this one.