{ "id": "AIBD-0078", "title": "Viz ICH Plus detects a parieto-occipital hemorrhage and auto-alerts the transfer team; 47-year-old moved between hospitals of a large urban health system in 101 minutes, mRS 1 at one year", "summary": "Viz ICH Plus flagged a 47-year-old's haematoma and alerted the transfer team; transfer in 101 min vs 199.7 average; mRS 1 at one year.", "date_observed": "2025-03-18", "date_basis": "unassessed", "date_precision": "unassessed", "benefit_status": null, "source_collection": null, "source_entry": null, "account": "A 47-year-old man came to the transferring hospital of the authors' large urban health system. He had severe headache, nausea and vomiting but no speech or motor deficits. The paper names neither the hospitals nor the city. All authors are at the Icahn School of Medicine at Mount Sinai, New York. Viz ICH Plus (Viz.ai) analyzed his computed tomography (CT), revealing a substantial right parieto-occipital haematoma with ventricular extension. It auto-alerted the Neuroemergencies Management and Transfer (NEMAT) team at the receiving specialized stroke center. With an ICH score of 2 he was transferred within 101 minutes across 13.7 miles, against an average interhospital transfer time of 199.7 minutes. He had supratentorial craniotomy with endoscopic haematoma evacuation and ventriculoperitoneal shunt placement. His scores were mRS 4 and NIHSS 6 at one month, 3 and 5 at three months. At one year: mRS 1 and NIHSS 2.", "category": "harm prevented", "unexpected": false, "purpose": "Viz ICH Plus is built to detect intracranial hemorrhage on non-contrast CT and automatically notify care and transfer teams. Faster interhospital transfer is its intended function.", "system": "Viz ICH Plus", "model_version": null, "developer": "Viz.ai", "deployer": "Large urban healthcare system, not named in the report; the city is not stated, and all authors are affiliated with Neurosurgery, Icahn School of Medicine at Mount Sinai, New York", "location": null, "domain": "Healthcare - neurosurgery / intracerebral hemorrhage", "segment": "AI hemorrhage detection with automated transfer notification", "benefit_type": "Improved Physical Health", "taxonomy_note": null, "registry_ids": {}, "ratings": [ { "group": "personal", "depth": 3, "reason": "After a hemorrhage with ventricular extension the patient improved from mRS 4 at one month to mRS 1 at one year. The AI's share is the time saved in transfer, the surgery being the treatment." }, { "group": "organizational", "depth": 2, "reason": "Interhospital transfer took 101 minutes against the system's 199.7-minute average, with the receiving team engaged before the patient left the first hospital." } ], "ai_role": { "status": "assessed", "statement": "The software detected the haematoma and auto-alerted the receiving team, which coordinated stabilization advice and transfer. A CT ordered for severe headache would have shown the bleed regardless, so the AI's contribution is the speed of notification and transfer. Dr Kellner discloses research grant support from Viz.AI among other companies. No author is a Viz.ai employee." }, "evidence": [ { "kind": "case report", "citation": "Afreen R, Ezzat B, Kalagara R, Dangayach NS, Kellner CP (2025). Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology. Cureus 17(3):e80790.", "title": "Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "date": "2025-03-18", "written_by": "deployer", "quote": "Viz ICH Plus analyzed the patient's CT, revealing a substantial right parieto-occipital hematoma with ventricular extension, and automatically alerted the Neuroemergencies Management and Transfer (NEMAT) team" }, { "kind": "case report", "citation": "Afreen R et al. (2025). Cureus 17(3):e80790 (second quotation).", "title": "Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "date": "2025-03-18", "written_by": "deployer", "quote": "With an ICH score of 2, the patient was transferred within 101 minutes across a 13.7-mile distance - much faster than the average IHT time of 199.7 minutes" }, { "kind": "case report", "citation": "Afreen R et al. (2025). Cureus 17(3):e80790 (third quotation, one-year outcome).", "title": "Optimizing Intracerebral Hemorrhage Management and Interhospital Transfer With Viz ICH Plus AI Technology", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "date": "2025-03-18", "written_by": "deployer", "quote": "one year, his scores had further improved to mRS 1 and NIHSS 2" } ], "replication": { "produced_by": [ "Viz ICH Plus running on CT scans at the transferring hospital with automatic notification to a centralized neuro-emergency transfer team", "A command-center workflow that coordinates stabilization advice and ambulance transfer" ], "must_hold": [ "A receiving center able to operate promptly", "Clinicians act on the automated alert rather than waiting for a formal radiology read" ], "echoes": [] }, "paired_incident": null, "headline": "Viz ICH Plus flags a haematoma; transfer in 101 minutes, mRS 1", "metric": "transfer in 101 min vs 199.7 average; mRS 1 at one year", "comparator": { "against": "the average interhospital transfer time for similar intracerebral hemorrhage cases, taken from a published New York City hospital-system cohort", "before": "199.7 minutes", "after": "101 minutes", "basis": "measured", "quote": "With an ICH score of 2, the patient was transferred within 101 minutes across a 13.7-mile distance - much faster than the average IHT time of 199.7 minutes for similar cases", "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/" }, "later": { "status": "unknown", "date": null, "note": "The report ends at the one-year outcome; nothing later was found in the cited source.", "quote": null, "url": null }, "value": null, "developer_country": "United States", "deployer_country": null, "unrated_because": null, "brief_notes": null, "brief": null, "revisions": [ { "date": "2026-10-20", "change": "Record drafted from the cited sources.", "source": null, "editor": "AIBD" }, { "date": "2026-10-20", "change": "Removed the New York placement from the title, account and deployer and set location to null, stating instead that the paper names neither the hospitals nor the city and that the authors are affiliated with the Icahn School of Medicine at Mount Sinai, New York, because the paper describes only “our large urban healthcare system” and the city had been inferred from the affiliation line.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Added what the benefit is measured against from the cited sources.", "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12006056/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Organizational Efficiency among the six first used.", "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Country of the developer added from the organization's own site or a registry.", "source": "https://www.viz.ai/privacy-policy", "editor": "AIBD" }, { "date": "2026-10-21", "change": "Prose pass: a rating reason, account, purpose, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.", "source": null, "editor": "AIBD" } ], "confidence": "claimed", "shade": "low", "claim_status": "The deployer's account", "claim_basis": "Sources: the deployer's case report. 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