Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
AI-driven predictive triage and population health management for high-precision clinical intervention.
Diagnostic Robotics provides a sophisticated AI-native clinical prediction platform designed to optimize healthcare ecosystem efficiency. Its 2026 market positioning centers on 'The Intelligence Layer' between patients and providers, utilizing deep learning models trained on billions of clinical data points and EHR records. The technical architecture employs a proprietary NLP engine for patient intake and advanced predictive modeling to identify high-risk patients before acute events occur. By integrating seamlessly with existing EHR systems via FHIR and HL7 standards, Diagnostic Robotics enables value-based care organizations to automate triage, reduce emergency department (ED) strain, and close care gaps with hyper-personalized interventions. The platform focuses heavily on 'Predictive Triage,' moving beyond simple symptom checkers to provide clinically validated risk scores that drive proactive outreach. As healthcare systems face extreme labor shortages in 2026, Diagnostic Robotics acts as a force multiplier for care teams by prioritizing cases based on clinical urgency and total cost of care impact, fundamentally shifting medical workflows from reactive to proactive.
Uses Bayesian networks and deep learning to assess the likelihood of specific diagnoses based on patient-reported symptoms and historical EHR data.
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive clinical and operational intelligence to fight death and waste in healthcare.
Predictive medical data and clinical insights for streamlined enterprise underwriting.
The professional medical network for clinicians, providing HIPAA-compliant AI and telehealth solutions.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Bi-directional data flow using SMART on FHIR protocols to surface risk scores directly within the clinician's view in Epic or Cerner.
ML algorithms scan claims and clinical notes to identify missing screenings, vaccinations, or follow-up visits.
Incorporates Social Determinants of Health (SDOH) data into predictive models to identify non-clinical risks like transport or food insecurity.
Natural Language Processing interface that collects patient symptoms via chat/voice and translates them into clinical terminology.
Analyzes post-discharge data to flag patients at highest risk of returning to the hospital within 30 days.
Allows health systems to adjust sensitivity/specificity levels based on their specific resource capacity.
Overcrowding in the ED due to non-urgent medical issues.
Registry Updated:2/7/2026
Appointment is booked automatically via API integration.
Payers failing to accurately predict and budget for high-cost members.
Nursing staff spending hours on phone calls to determine patient urgency.