Our Technical Approach
MitiHealth AI pioneers a transformative approach to precision risk assessment for clinical harm events, integrating advanced machine learning and deep learning techniques with rich clinical data sources, including electronic health records (EHRs) and historical patient data.
Our platform seamlessly aggregates longitudinal patient records, encompassing comprehensive medical histories, lab results, diagnostic reports, and physician notes. We leverage tailored state-of-the-art deep neural networks to model temporal dependencies within patient data, ensuring a nuanced understanding of disease progression and response to treatment.
By utilizing attention mechanisms, our models prioritize critical clinical features, such as anomalies in vital signs or laboratory values, which often precede adverse events. Natural language processing (NLP) capabilities further unlock insights from unstructured clinical narratives, empowering our AI system to distill patient-specific risks with exceptional granularity.
This integration of clinical data, EHRs, and deep learning technologies enables our platform to offer timely, data-driven alerts to caregivers, facilitating proactive interventions that have the potential to significantly enhance patient outcomes.