Healthcare AI Focus Areas
We focus on practical, regulatory-aligned healthcare AI applications, supporting real-world validation and adoption through a PoC-first pathway.
In Taiwan, oncology provides a clearly structured and policy-aligned entry domain. However, our scope extends across broader healthcare AI applications beyond cancer.
How We Define Focus Areas
From Technology Categories to Adoption Domains
We do not define focus areas by algorithms or model types. Instead, we assess healthcare AI applications based on:
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Clinical relevance
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PoC feasibility
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Regulatory clarity
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Scalability within healthcare systems
Focus Areas
Cancer & Oncology AI
Primary Entry Domain in Taiwan
Cancer remains the leading cause of death in Taiwan, with a well-defined spectrum of prevalent cancers including lung, colorectal, breast, liver, prostate, oral cavity, thyroid, skin, gastric, and corpus uteri cancers.
These domains provide clear and diverse entry points for AI deployment across imaging, screening, and clinical decision support.
Medical Imaging AI
High Readiness for Market Entry
Medical imaging remains one of the most mature AI application domains in healthcare.
In Taiwan, imaging-based AI solutions benefit from well-established workflows and data availability.
However, successful deployment depends on integration with clinical processes and clear positioning as assistive—not substitutive—tools.
Clinical Decision Support
Regulatory-Sensitive Domain
AI-based clinical decision support systems offer high potential impact in diagnosis and treatment planning.
These applications require careful alignment with clinical responsibility, explainability, and regulatory boundaries.
TFDA classification and intended use definition are critical for deployment.
Risk Stratification & Screening AI
PoC-Friendly Deployment Domain
AI-driven risk stratification and screening models support early detection and preventive care.
These applications are often well-suited for PoC-first deployment, particularly within structured screening programs and population health initiatives.
Workflow Optimization & Clinical Triage
Low Regulatory Barrier, High Operational Impact
AI solutions focused on workflow optimization improve efficiency in triage, prioritization, and resource allocation.
These applications are often non-SaMD and can be deployed with fewer regulatory constraints,
making them a practical entry point for early collaboration with healthcare institutions.
Across All Domains
A Common Pathway
Regardless of application area, we apply a consistent PoC-first, regulatory-aligned pathway to support structured and scalable adoption within Taiwan’s healthcare system.
Cancer-related AI applications often present a clear clinical demand and strong policy alignment, making them a common entry point for healthcare AI in Taiwan
Primary Adoption Domain
Medical imaging remains one of the most mature AI application areas, yet also one of the most workflow-sensitive. We focus on alignment with clinical processes and clarity of assistive—not substitutive—roles
Medical Imaging AI
CDS solutions offer high potential impact but require careful positioning, interpretability, and regulatory boundary definition
Clinical Decision Support (CDS)
These applications support preventive care and population health, with emphasis on integration into existing screening and care pathways.
Risk Stratification & Screening AI
Not all impactful AI participates in diagnosis. Workflow-oriented AI can significantly improve efficiency, resource allocation, and clinical prioritization
Workflow Optimization & Clinical Triage
Regardless of application domain, we apply the same PoC-first, regulatory-aligned market entry pathway to support sustainable adoption in Taiwan