Flow Immersive for Healthcare

Flow has been used extensively in population health use cases, gaining popularity showing COVID19 datasets.

3D/VR/AR visualization and AI driven analysis can facilitate the detection and management of adverse events. The technical execution of medical data review using AI and VR/AR gives benefits like interactive dashboards, immersive analysis, collaborative review, real-time data overlay, outlier detection, trend identification, signal detection, and predictive analytics.
COVID Genetic variants and spread across the globe

Pharmaceutical and Medical Review Use Cases

A smart combination of 3D/VR/AR data visualisation with a user-voice guided analytical AI allows quick and valid analyses of the data. This way outlier or significant results can be identified very easily even by users that are neither statisticians nor subject matter experts.
Project for US National Cancer Institute: 3D/VR visualization of the distribution of several Biomarkers on a cancer tissue sample. Note: Select biomarkers (left side) from a long (30+) list using a hierarchical 3D menu to show (center) elevated 3D dots indicating relative strength (height) of that biomarker per cell.

AI changes almost everything

End users can ask contextual questions surrounding any data point (from a reference pdf, or general knowledge), manipulate visualizations on the fly, encouraging infinite exploration and discovery.
When creating Flows, AI speeds up the creation process through suggested visualizations and insights.

Building with AI
The fusion of AI and AR/MR empowers us to unlock greater potential of our cognitive abilities, enabling us to solve complex problems, make informed decisions, and share insights with colleagues.

Flow applies six meaningful functions in our AR/MR + AI data visualization platform:
To learn more, please read this AR Insider article written by our founder Jason Marsh, and contact us below!
  1. Spoken commands simplify the user interface
  2. The LLM explains and provides context that goes beyond the data
  3. Create and manipulate visualizations
  4. User-uploaded PDF documents ensure expert content-specific accuracy
  5. Manipulate the underlying data through AI-generated Python scripts
  6. “What should I notice about my data?” identifies trends & outliers, correlations, and insights
AI + AR is magic
AI makes AR more useful, and overcomes some core limitations of AR, which include a constrained field of view within which it is difficult to include more than one panel of UI buttons and interactions.

The inverse is also true: AR helps AI to be more concrete. In the context of data visualization, LLMs can identify how to process massive amounts of data quickly, identify patterns, and present insights, but the results are usually limited to text. On the other hand, AR can provide an interactive, immersive platform to visualize these insights and/or anchor the insights within the larger context of the scope of the data.

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