Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.

The collective intelligence system for the world's medical expertise.
The Human Diagnosis Project (Human Dx) is a worldwide effort to map the world's medical knowledge by building a collaborative intelligence platform. By 2026, Human Dx has solidified its position as the foundational ground-truth layer for clinical reasoning, bridging the gap between human expertise and generative AI. The platform operates on a consensus-driven model where clinicians contribute, solve, and peer-review complex medical cases. Its technical architecture utilizes a structured knowledge graph that converts unstructured clinical observations into standardized diagnostic paths. This dataset is increasingly utilized by health systems and AI developers to benchmark Large Language Models (LLMs) against human clinical reasoning. The project is led by a 501(c)(3) nonprofit, ensuring that the collective intelligence remains a public good. Its 2026 market position focuses on 'Clinical Intelligence Validation,' providing a verified environment where medical students, residents, and attending physicians can sharpen their diagnostic skills while simultaneously contributing to a global database of medical logic that powers the next generation of safe, evidence-based healthcare AI.
Aggregates independent diagnostic opinions from thousands of clinicians to produce a single, weighted consensus.
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.
A daily clinical reasoning challenge delivered via push notification, mapped to standardized medical curricula.
Calculates the 'Diagnostic Differential Index' based on the breadth and accuracy of a user's differential.
Maps symptoms, findings, and diagnoses into a machine-readable graph for AI training.
A double-blind system for verifying the accuracy of submitted medical cases.
Automatically tracks and exports Continuing Medical Education credits based on participation.
Allows cases to be solved by multi-specialty teams to address complex, comorbid patients.
Residents need a standardized way to practice clinical reasoning outside of direct patient care.
Registry Updated:2/7/2026
Faculty reviews aggregate resident performance data.
A solo practitioner in a remote area lacks immediate access to specialists for complex cases.
AI developers need to know if their medical LLM is halluncinating or providing accurate clinical logic.