OncoBrain is an oncology‑specific clinical reasoning engine that ingests structured and unstructured patient data and generates peer‑level, explainable treatment recommendations grounded in NCCN, ASCO and peer‑reviewed literature. By delivering real‑time, guideline‑concordant insights with traceable evidence and a sub‑1% hallucination rate, it augments oncologists’ decision‑making at the point of care while preserving clinician judgment.
Funding
Funding not disclosed
Founders
Product
Problem
Oncologists must keep up with continuously updated guidelines and vast medical literature, yet most clinicians lack real-time access to subspecialty expertise and struggle to synthesize this information into patient‑specific treatment decisions.
Solution
OncoBrain offers an oncology‑specific clinical reasoning engine that ingests structured and unstructured patient data—including records, imaging, and pathology—and processes it with a proprietary inference layer trained on over one million cases. The system generates peer‑level, explainable recommendations grounded in NCCN, ASCO, and peer‑reviewed literature, presenting guideline‑concordant options at the click of a button while preserving clinician judgment. Multiple verification loops and patented hallucination‑detection algorithms keep the hallucination rate below 1%, ensuring safety and reliability. Full traceability links each suggestion to its source evidence, providing transparency for clinicians to validate and trust the output. Deployed in a private‑cloud, HIPAA‑compliant environment, OncoBrain acts as a clinical assurance layer that speeds decision‑making without replacing the physician.
Target Audience
Primary users are oncologists, hematologists, and multidisciplinary cancer care teams in community hospitals, health systems, and academic centers that need rapid, guideline‑aligned decision support at the point of care.
Features
- Ingests both structured and unstructured clinical data from electronic health records, imaging, and pathology reports
- Oncology‑specific inference engine trained on >1 M patient cases for high‑accuracy reasoning
- Explainable, traceable recommendations linked to NCCN, ASCO, and peer‑reviewed sources
- Patented hallucination detection and multiple verification loops achieving <1% hallucination rate
- Human‑in‑the‑loop design that augments, not replaces, clinician judgment
- Enterprise‑ready private cloud deployment with full data ownership and HIPAA compliance