Qais Amro@qaisamro

Clinical Copilot is a real-time, multi-agent AI system designed to solve one of healthcare's most pressing problems: diagnostic errors and documentation burden. The system ingests a raw doctor–patient conversation and, within seconds, runs a 5-stage intelligent pipeline: entity extraction, clinical reasoning, safety validation, documentation generation, and confidence calibration. Unlike generic chatbots, Clinical Copilot operates as a specialized medical reasoning engine. Each stage is handled by a dedicated AI agent with a specific clinical role: - The Extraction Agent identifies symptoms, vitals, medications, and patient history from the conversation. - The Reasoning Agent generates a ranked differential diagnosis list and flags emergency red flags. - The Safety Agent performs drug interaction checks, hallucination detection, and generates automated clinical warnings. - The Output Agent produces professional SOAP notes and ICD-10 diagnostic codes with clinical reasoning. - The Validator calibrates a confidence score based on available evidence quality. All outputs are formatted as FHIR R4-compatible JSON, making the system directly integrable with hospital EHR platforms like Epic or Cerner. The frontend is a hospital-grade React dashboard that showcases the live agent pipeline, structured clinical cards (Diagnosis, SOAP, Safety, ICD-10, FHIR), and a real-time confidence meter. Clinical Copilot targets two core healthcare problems: reducing diagnostic errors and accelerating documentation. Physicians spend up to 50% of their time on paperwork. This system cuts that to seconds while adding a safety validation layer that reduces missed diagnoses. The system is designed as a step toward autonomous, explainable, and safe AI assistance embedded directly inside real healthcare workflows.

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