AI Center Hualien Tzu Chi Hospital
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About

Our role in the hospital

The AI Center is the hospital's dedicated unit for coordinating AI development, working across every department and team to bring AI projects to life and consolidate results. The Center is not just a technology developer — it's a bridge connecting clinical needs, information systems and data governance, helping departments turn AI ideas into services that actually run.

In application, the Center's work spans medical image interpretation, clinical decision support, NLP-based chart analysis, smart scheduling and resource allocation, customizing models and interfaces to each department's real needs — ensuring AI tools genuinely fit clinical workflows rather than remaining proofs of concept.

In practice, every project goes through the full cycle — needs interviews, data preparation, model development, clinical validation and go-live — with continued tracking of post-launch usage and model performance to keep AI services running stably, gradually expand adoption, and feed learnings back into the next round of development.

Focus areas

Four areas we work in

  • Medical imaging AI

    Introduces image-interpretation assist models, speeding up reading for Radiology and related departments.

  • Clinical decision support

    Combines chart and lab data to provide risk alerts and treatment-suggestion references.

  • Mobile services

    Extends AI features to mobile devices, supporting real-time use at nursing stations and the point of care.

  • Data governance & analysis

    Establishes standardized data pipelines as the foundation for the long-term iteration of AI models.

Core objectives

Sustainable management, building a smart hospital

Built on four core pillars that underpin the Center's long-term operation and the hospital's AI capability-building.

  1. 01

    Medical data integration

    Integrates healthcare data so it can flow and be put to use.

    Goal Integrates scattered hospital data so it can be found, put to use, and safely exchanged and shared.

  2. 02

    AI & smart workflows

    Introducing AI, machine learning and agentic workflows.

    Goal Brings AI into clinical workflows, automating tasks, improving efficiency, and making care smarter.

  3. 03

    AI talent development

    Drives the accumulation of in-house AI capability and training.

    Goal Builds staff AI literacy — so more people understand AI, can use it, and can apply it to their actual work.

  4. 04

    AI governance & risk management

    Establishes quality, risk and governance mechanisms for data and AI applications.

    Goal Ensures data and AI are used correctly, safely and reliably, so AI innovation can grow soundly within a healthcare setting.

Organization

Organisation chart

The Center is directed by a Deputy Superintendent, supported by five deputy directors, six specialist teams and a project-management and administrative team. Select a team to see its cases.