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TEXXR

Chronicles

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Google Cloud expands Vertex AI Search with features to help health care workers pull info from clinical notes, scanned documents, and electronic health records

Ashley Capoot / CNBC :

CNBC Ashley Capoot

Context & Ripple Effects

Google Cloud’s health-care AI push has moved from data foundations toward clinician-facing retrieval. Its Cloud Healthcare API rollout focused on making patient data interoperable, while Vertex AI provided the managed platform on which developers could deploy models.

The company had already tested health-care search and chatbot workflows with Mayo Clinic; this expansion of that Mayo Clinic collaboration’s search use case brings the effort closer to the unstructured records clinicians work with, including notes and scans.

First-order effects

  • Health-care workers using Vertex AI Search can retrieve information across clinical notes, scanned documents and electronic health records through a single product surface.
  • Google Cloud broadens Vertex AI Search from a general AI-search offering into a more specialized health-care workflow, extending the utility of its existing Vertex AI platform.

Second-order effects

  • Health systems evaluating AI search tools gain a cloud-native option that ties retrieval to the clinical data formats they already manage, raising the importance of interoperability and document-ingestion capabilities in vendor selection.
  • Competing cloud and health-IT suppliers face pressure to support both structured electronic records and unstructured clinical material rather than treating search as a standalone chatbot feature.

Third-order effects

  • If these tools prove usable in clinical settings, health-care AI competition could shift from isolated diagnostic models toward platforms that connect models, search and longitudinal patient data in everyday workflows.
  • That transition would make dependable data normalization and access controls more central sources of differentiation, building on the industry’s earlier emphasis on interoperable health data.

The trend: Health-care AI is evolving from point tools into cloud platforms that make fragmented clinical information searchable within operational workflows.

Discussion

  • @aashimatweets Aashima Gupta on x
    #HLTH23 Pleased to announce @googlecloud's Vertex AI Search features for healthcare and Life Sciences, it will help make it easy for nurses and clinicians to find the information they need faster. https://cloud.google.com/...
  • @googlehealth @googlehealth on x
    📣 Watch a captivating conversation about the transformative power of AI in healthcare. 🏥🤖 @jhalamka, President of the Mayo Clinic Platform, and Google's Head of Health AI, Greg Corrado, delve into the potential of generative AI for health.
  • @ashleycapoot Ashley Capoot on x
    New: @googlecloud announced time-saving AI search capabilities that aim to help health-care workers quickly pull accurate clinical information from different types of medical records. I chatted w/ the folks at Google and early adopters to learn more: https://www.cnbc.com/...
  • @medtechcate Catherine Longworth on x
    How can we bring AI to healthcare responsibly? @Google SVP James Manyika says data privacy is going to be an important topic to tackle as technology evolves and questions around data privacy continue to shift #HLTH2023 @Healthcare_GD [image]
  • @joshuapliu Joshua Liu on x
    Google VP: “who are the top 5 AI companies? Only 2 are big companies: - google - Microsoft - openAI - anthropic - cohere” Not including Meta here is a major oversight IMO... #HLTH2023
  • r/CLOV r on reddit
    Google announces new generative AI search capabilities for doctors