HemoVision-AI
Multimodal Hemostasis
Bridging Static Data & Dynamic Surgical Reality
A proprietary multimodal system that correlates blood panels, medical reports, and real-time surgical video to predict bleeding risks and monitor intra-operative blood loss—all processed locally with complete data sovereignty.
Why Surgical Hemostasis Needs Private AI
Surgical hemorrhage remains a leading cause of preventable mortality. A critical disconnect often exists between a patient's blood chemistry (static reports) and the surgical reality (live video of tissues).
HemoVision-AI bridges this gap by ingesting and correlating blood panels (CBC, Coagulation), unstructured medical reports, and real-time surgical video feeds—ensuring sensitive patient biomarkers and surgical footage remain secure within your infrastructure.
Target Users
Anesthesiologists
Data Types
Multimodal
EBL Accuracy
>95%
Deployment
Edge-AI
The Static vs. Dynamic Gap
Understanding the critical disconnect that makes surgical hemostasis monitoring essential for Private AI.
Fragmented Data
Important clues about bleeding risk are often buried in unstructured PDF medical reports or external lab results that surgeons must mentally synthesize.
Mental Synthesis RequiredSubjective Blood Loss
Surgeons and anesthesiologists currently estimate blood loss visually ('eyeballing'), which is notoriously inaccurate and leads to delayed interventions.
Notoriously InaccurateVideo Privacy Risks
Surgical video recordings contain biometric identifiers (internal anatomy, faces of staff) and require immense storage security, making cloud analysis risky.
Biometric IdentifiersELMET HemoVision-AI Capabilities
A Multimodal Model that combines Natural Language Processing (NLP) for reports with Computer Vision (CV) for surgical video.
"Blood-NLP" Engine
Parses heterogeneous documents (PDFs, scanned labs, external hematology consults). Normalizes data like INR, PTT, Platelet function, and extracts keywords like 'Von Willebrand history' or 'Anti-platelet therapy.'
Surgical Computer Vision
Analyzes live video (Laparoscopic/Robotic/Open cameras). Detects Active Bleeding (arterial spurts vs. venous oozing), smoke density (cautery use), and surgical phases.
Hemodynamic Correlation
The 'Brain' of the system. Cross-references video analysis with blood reports. Example: If video shows micro-oozing and NLP recalls 'Low Fibrinogen,' it alerts for Cryoprecipitate transfusion.
Automated Surgical Auditing
Post-surgery, analyzes the full video to generate a 'Surgical Safety Report,' flagging moments of instability or technique deviation for quality improvement.
The "Smart" Operating Room
How HemoVision-AI transforms surgical workflow through three critical phases.
The "Read"
The AI scans the patient's entire Electronic Health Record (EHR), identifying hidden risks across years of medical history.
Example Insight:
Flags a PDF report from 3 years ago mentioning a "minor reaction to Heparin" and correlates it with current blood work showing borderline platelets.
Output
A "Coagulation Risk Score" is generated for the Anesthesiologist before the first incision.
The "Watch"
Live Video Analysis
As the surgeon operates, the AI measures the surface area of blood in the sterile field frame-by-frame to calculate Real-Time Estimated Blood Loss (EBL) with >95% accuracy compared to gravimetric methods.
Smart Alert Example
"Visual bleeding pattern consistent with Coagulopathy, not surgical trauma. Pre-op PTT was borderline high (38s). Recommend checking ACT or administering FFP."
The "Learn"
Generates a video highlight reel of "Critical Events" (e.g., moments of high bleeding)
Updates patient file with granular report on tissue handling and hemostasis performance
The "Private AI" Architecture
Given the sensitivity of genomic blood data and raw surgical video, ELMET deploys HemoVision-AI as a Sovereign AI instance.
Edge-AI Processing
Video analysis occurs on ELMET hardware inside the Operating Room (OR) rack. No video stream ever leaves the OR network.
Zero Video EgressPrivate LLM
The NLP engine interpreting medical reports is a distilled, domain-specific model hosted on the hospital's internal server. No API calls to public models.
No External APIsZero-Knowledge Training
Model improves bleeding detection accuracy using federated learning across hospital sites without sharing patient video or names—only weight updates are shared.
Federated LearningTailored for Every Stakeholder
HemoVision-AI integrates seamlessly into existing hospital workflows for all team members.
For the Pathologist/Hematologist
Instead of reviewing hundreds of raw blood values, they receive an AI-summarized "Hemo-Dashboard" prioritizing patients with conflicting data (e.g., normal labs but clinical history of bleeding).
For the Surgeon
An unobtrusive "Heads-Up Display" (HUD) on the surgical monitor showing real-time EBL and Coagulation Status without disrupting surgical flow.
For the Hospital Admin
Automated coding for billing. The AI confirms "High Complexity" due to specific complications identified in video and reports, ensuring accurate reimbursement.
Transforming Surgical Outcomes
Measurable improvements across patient safety, resource management, and legal compliance.
Patient Safety
Early detection of Disseminated Intravascular Coagulation (DIC) by correlating visual cues with lab trends hours before systemic collapse.
Hours Earlier
DIC Detection
Resource Management
More accurate blood loss tracking reduces unnecessary blood transfusions, saving the hospital money and preserving blood bank supply.
Reduced
Unnecessary Transfusions
Legal & Compliance
An objective, AI-generated log of the surgery and pre-op analysis provides robust defense against malpractice claims regarding surgical error vs. physiological inevitability.
Complete
Audit Trail
Related Resources
Explore more about multimodal AI in healthcare and surgical intelligence.
Multimodal AI in Surgical Hemostasis: Real-Time Blood Loss Intelligence
How AI systems that correlate blood chemistry with live surgical video are transforming intra-operative monitoring.
Read ArticleCase StudyRegional Hospital Reduces Surgical Complications with HemoVision-AI
How a 450-bed regional hospital achieved 40% reduction in blood transfusion errors using AI-powered hemostasis monitoring.
View Case StudyReady to Transform Surgical Intelligence?
Discover how HemoVision-AI can bring real-time hemostasis monitoring to your surgical teams with complete data sovereignty.