Viz Training AI Stroke Care 3.1.0

Viz.ai, Inc. – Freeware – iOS
out of 16 votes

Synchronize stroke workflow at your hospital efficiently using Viz. This AI-powered solution automatically detects suspected strokes on brain imaging and promptly triages cases to your device, facilitating seamless coordination from any location.

Viz is designed to revolutionize global healthcare delivery by leveraging intelligent software to streamline physician notification times and enhance care accessibility. In 95% of verified cases, Viz LVO accelerates the alert process for neurovascular specialists regarding potential large vessel occlusion strokes, outperforming standard care by averting an average delay of 52 minutes.

Upon receiving a positive notification, users can securely access patient stroke imaging (including CT perfusion color maps), gather clinical background, contact referral facilities, send HIPAA-compliant texts, and more – all conveniently via their mobile devices.

Viz Training serves as an informative tool and is not classified as a medical device. For further information, please reach out to Viz.ai at [email protected].

Overview

Viz Training AI Stroke Care is a Freeware software in the category Home & Hobby developed by Viz.ai, Inc..

The latest version of Viz Training AI Stroke Care is 3.1.0, released on 05/05/2024. It was initially added to our database on 05/05/2024.

Viz Training AI Stroke Care runs on the following operating systems: iOS.

Users of Viz Training AI Stroke Care gave it a rating of 5 out of 5 stars.

Pros

Improves workflow efficiency in stroke care teams.
Utilizes AI to rapidly analyze CT scans, decreasing time to treatment.
Enhances communication among medical staff via shared insights and real-time notifications.
Empowers healthcare providers with actionable data for better decision-making.
Reduces the likelihood of human error in diagnosing strokes.

Cons

May require significant initial investment for healthcare facilities.
Relies heavily on data quality and availability, which may vary across institutions.
Potential challenges in integration with existing hospital systems and workflows.
Users may need extensive training to effectively use the application.
Concerns about patient data privacy and compliance with regulations.

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