See how we produce optimal AI solutions for our clients.
Cardiovascular diseases (CVDs) are a major global health concern, accounting for a significant number of deaths each year and being a leading cause of mortality worldwide. Accurate and timely diagnosis of CVDs is crucial for effective treatment and improved patient outcomes. The gold standard used for screening and diagnosing CVDs is Electrocardiography (ECG). However, accurately interpreting ECG results can be challenging for healthcare professionals. In this case study, we explored the implementation of Machine Learning (ML) for ECG recognition to enhance diagnostic accuracy and enable timely interventions.
Published: January 22, 2025A private research organization focused on evaluating the safety and effectiveness of medications. Their goal is to use advanced data analysis to support healthcare decisions and meet regulatory standards. For this project, they aimed to assess the safety of hydroxychloroquine, used alone or with azithromycin, for treating rheumatoid arthritis. The study focused on identifying short-term side effects and long-term risks, especially related to heart health and the use of multiple medications together. The client needed a data-driven approach to fill gaps in existing evidence by combining different clinical data sources, identifying patient groups with similar characteristics, and addressing factors that could affect treatment outcomes.
Published: January 21, 2025Large data volumes are revolutionizing industries, including medical research. This influx of data enables observational studies that harness global statistical evidence. However, conducting such studies can be labor-intensive and prone to inconsistencies due to disconnected communication channels, like repositories, emails, forums, and chats. Moreover, adapting code to different environments during the execution phase can create unscalable and non-reusable analytical frameworks. In response, the OHDSI community is developing ARACHNE, an innovative platform designed to streamline observational research by fostering collaboration among life sciences, healthcare, academia, and organizations handling patient-level data.
Published: January 16, 2025The OMOP CDM is widely recognized as the industry standard for observational health research. It provides a standardized data model that facilitates data integration and sharing across different sources, enabling researchers to conduct studies at scale. ATLAS is a central tool used for research within the OMOP CDM ecosystem, providing a user-friendly interface for querying the data model and creating visualizations. Building well-defined cohorts is a critical first step in conducting research using the OMOP CDM. By selecting and defining cohorts of patients with specific characteristics or conditions, researchers can ensure that their studies are focused and relevant, and can generate reliable evidence.
Published: January 16, 2025We 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.
Published: January 16, 2025The 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.
Published: November 28, 2024The language learning platform adapts to each user’s progress, providing customized exercises and challenges. Gamification features like leaderboards, badges, and progress tracking make learning more engaging and enjoyable. From basic vocabulary to complex scripts like Mandarin and Arabic, the platform makes language learning both fun and effective.
Published: October 13, 2024Our 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.
Published: August 15, 2024A web application designed to facilitate communication in psychopathology treatment by summarizing mental health test results and illustrating treatment dynamics.
Published: June 25, 2024Jackalope transforms complex medical data into OMOP CDM and SNOMED Clinical Terms (CT) standardized formats. This enables healthcare providers, practitioners, and scientists to effectively use real-world medical data for research and delivering enhanced patient care.
Published: April 29, 2024