Information processing device and information processing system
The integration of personal and non-personal health data through a large-scale language model in a secure system provides personalized health advice, addressing individual health needs and ensuring privacy and security.
JP2026073692AActive Publication Date: 2026-05-01PHENOGEN MEDICAL INC
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- PHENOGEN MEDICAL INC
- Filing Date
- 2024-10-18
- Publication Date
- 2026-05-01
AI Technical Summary
Technical Problem
Traditional health management systems fail to fully utilize individual health data and are limited to general health advice, lacking adequate addressing of individual health conditions and risks, with data privacy and security issues remaining challenges.
Method used
An information processing device and system that utilizes a large-scale language model to provide personalized health advice by integrating personal health data with non-personal information, ensuring data privacy through separate databases and secure communication protocols.
Benefits of technology
Enables real-time personalized health management and disease prevention advice with high accuracy while protecting user privacy and securing data management.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure 2026073692000001_ABST
Abstract
To provide an information processing device and information processing system that can provide health advice reflecting individual health data, while appropriately addressing data privacy protection and security issues. [Solution] An information processing device equipped with a control unit, the control unit comprises a search extension generation unit that generates inference requests to be input to a machine-learned large-scale language model based on input information including personally identifiable information that can identify an individual, and a transmission / reception unit that transmits inference requests to the large-scale language model and receives inference results from the large-scale language model, wherein the search extension generation unit generates inference requests influenced by personally identifiable information based on a first search result obtained by searching a first database in which first information linked to an individual identified by personally identifiable information is stored, and a second search result obtained by searching a second database in which second information consisting of non-personal information is stored.
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Citation Information
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