Helping Hospitals Go Smart — AcceleratingSmart HealthcareAdoption

New Taipei (NT Medical Association) — Healthy Taiwan Cultivation Plan Case Study

New Taipei Medical Association — Specialties：Primary Healthcare

Plan Name: New Taipei 888 Three-High & Cardio-Renal Disease Prevention Mobile Digital Healthcare AI Platform

Plan No.: A2-0022

I. Hospital Needs

Led by the New Taipei Medical Association, this initiative targets primary clinics' patients with the three highs (hypertension, hyperglycemia, hyperlipidemia) and cardio-renal disease, deploying a digital healthcare AI platform. Primary clinics lack digital management tools, and continuity of care for chronic three-high patients is insufficient — necessitating AI-assisted tools to improve diagnosis efficiency and research capacity. The plan also incorporates a large-scale cluster randomized clinical trial design to validate the platform's clinical impact.

II. Key Benefits

• Improved Diagnostic Efficiency：AI-assisted tools reduce the workload on primary care physicians, shortening fundus and ECG interpretation time
• Better Three-High Chronic Care：Digital platform offers continuous tracking, effectively improving medication adherence and health metric control
• Clinical Trial Capacity：Builds primary care teams' real-world data collection and clinical trial capability, producing high-quality research
• Large-Scale Validation：Through cluster randomized trial design, scientifically validates the actual clinical benefits of the digital AI platform
• Policy Diffusion Potential：Outcomes can serve as a national reference model for digital transformation of primary clinics, scalable to other regions

III. Pain Points Addressed

Tainan (Tainan AI Colorectal Screening) — Healthy Taiwan Cultivation Plan Case Study

Tainan Medical Association — Specialties：Primary Healthcare

Plan Name: Tainan AI Colorectal Screening — Colorectal Cancer Expanded Screening & Treatment × AI Referral Smart Platform Enhancement Plan

Plan No.: A2 (Cross-Hospital Alliance)

I. Hospital Needs

Led by the Tainan Medical Association, in collaboration with the Tainan City Government Health Bureau, NCKU Hospital, Chi Mei Hospital, An Nan Hospital, Tainan Municipal Hospital, Sinlau Hospital, MOHW Tainan Hospital, and Kuo General Hospital — seven major medical institutions jointly promote colorectal cancer screening enhancement and smart referral governance optimization. Tainan's colorectal cancer screening rate is only 37% (below the national average of 42%), with insufficient colonoscopy completion rate for positive cases, plus broken information flow between primary clinics and hospitals — making an integrated digital referral and screening governance platform essential.

II. Key Benefits

• Higher Screening Rate：Through proactive recall and behavioral incentive design, expected to raise Tainan's colorectal screening rate to 50%+
• Shorter Diagnosis Time：Significantly shortens wait time from FIT-positive to colonoscopy completion, reducing case follow-up dropouts
• Digitized Referral Process：Primary clinics can track case progress in real time after referral, eliminating manual communication and information loss
• Cross-Hospital Data Integration：Seven hospitals and primary clinics share screening and referral data through unified platform, supporting health bureau policy evaluation
• Rural Coverage：Mobile medicine demonstrations and community participation mechanisms improve screening accessibility for rural and underserved populations
• Scalable Model：Modular platform design — can be extended to breast cancer, oral cancer, and other cancer screening domains in the future

III. Pain Points Addressed

Shin Kong Hospital — Healthy Taiwan Cultivation Plan Case Study

Shin Kong Hospital — Specialties：Radiology

I. Hospital Needs

As the number of AI models continues to increase, Shin Kong Hospital's radiology department faces the dilemma of fragmented multi-vendor model management. Each vendor's AI workflow and interface is independent, forcing physicians to switch between multiple systems to view all interpretation results — severely impacting diagnostic efficiency. The RIS system cannot display AI text interpretation results, and critical cases lack automated prioritization. Moreover, as a central hospital, Shin Kong needs to support cross-hospital AI imaging interpretation services for surrounding satellite institutions.

II. Key Benefits

• Unified AI Management：All radiology AI models centralized on a single platform, dramatically reducing management complexity and hardware footprint
• Improved Reporting Efficiency：Physicians can directly reference AI interpretation results within RIS without switching systems, significantly shortening report writing time
• Critical Case Priority Handling：AI automatically prioritizes critical images, ensuring high-risk cases are interpreted and reported first
• Lung Cancer Screening Compliance：Case managers generate reports compliant with HPA's Lung-RADS format directly through the system, eliminating manual entry burden
• Cross-Hospital AI Service：Satellite hospitals can access Shin Kong's AI platform interpretation support without building their own AI infrastructure, improving regional medical quality

III. Pain Points Addressed

Family Healthcare Record (FHR) App — Application Case

FHR — Specialties：Radiology

I. Hospital Needs

• Paperless & ESG Green Healthcare Transition：Aligned with national health initiatives and Deep Cultivation Plan benchmarks, hospitals urgently need to replace traditional CD burning and printed records to reduce carbon footprints.
• Patient-Centric Digital Services：Elevate patient satisfaction by providing instant, secure access to personal diagnostic images and medical records directly on personal devices.
• Low-Barrier Cloud Adoption：Require a SaaS-based subscription solution that fully qualifies under the 70% Operational Budget (OpEx) allocation of the Deep Cultivation Plan.

II. Key Benefits

• Mobile Image Access & Management：Patients can view, store, and manage their personal diagnostic images and records directly on mobile devices (iOS/Android).
• Elimination of Optical Disks & Reduced OpEx：Eliminates CD media, printing consumables, administrative processing overhead, and counter wait times.
• High-Speed Cloud Transfer：Powered by AWS cloud infrastructure and point-to-point transmission to ensure smooth and secure data delivery.
• OpEx Budget Compliance：The subscription-based app model avoids CapEx hardware hurdles and seamlessly utilizes operational grant budgets.

III. Pain Points Addressed

IV. Application Scenarios

• Front Desk & Radiology Image Release：Upon completing imaging exams at radiology or health checkup centers, patients scan a QR code to sync images directly to the FHR app.
• Outpatient & Inter-Hospital Referrals：Patients display high-resolution diagnostic images on their smartphones during consultations at other clinics or specialist centers.
• AWS Cloud AI Integration Output：AI-generated diagnostic insights can be delivered to patients via FHR for clear, intuitive doctor-patient communication.

Ubiquitous Diagnostic Environment (UDE) App — Application Case

UDE — Specialties：Neurology、Radiology

I. Hospital Needs

• Mobile & Unbound Diagnostics：Physicians require FDA Class II certified diagnostic tools during ward rounds, emergency care, or remote consultations.
• Cost-Effective AI Deployment for Regional Hospitals：Access AI-assisted diagnostics and an ultra-lightweight AI gateway without purchasing expensive local GPU servers.
• Rigorous Cybersecurity & Privacy Protection：Ensure full compliance with privacy regulations and medical security standards when transferring images to the cloud or across institutions.

II. Key Benefits

• All-in-One Mobile Diagnostic Station：Transforms an iPad Pro into an independent DICOM server, viewer, display, and AI workstation with FDA Class II diagnostic clearance.
• Instant Sharing & Edge AI：Supports QR code and AirDrop image sharing, integrated with Apple Core ML for local edge computing.
• Patented De-identification & DMZ Security：Automated batch removal of patient health information (PHI) combined with a DMZ network architecture guarantees zero privacy risks.
• 100% OpEx Alignment：Delivered as a turnkey iPad + UDE App subscription, requiring no server room construction and seamlessly utilizing operational grant funds.

III. Pain Points Addressed

IV. Application Scenarios

• Smart Mammography Bus：Screening images are transmitted via 5G to UDE for edge-AI processing, reducing report turnaround time by two-thirds.
• Outlying Island Telemedicine：Endoscopy images taken at remote clinics are sent to medical center AI servers via UDE, shortening diagnostic wait times from weeks to minutes.
• Emergency & Cross-Department Consultation：ER clinicians scan QR codes on iPads to review high-resolution images and AI alert overlays instantly.
• AI Clinical POC Gateway：Functions as a lightweight gateway for multi-center clinical validations and Proof of Concept (POC) testing.

AI Platform — Application Case

AI Platform — Specialties：Radiology、Hospital Governance Center

I. Hospital Needs

• Achieving Deep Cultivation Smart Healthcare KPIs：Hospitals need to rapidly deploy TFDA/FDA-cleared commercial AI models to meet grant evaluation standards.
• Multi-Specialty Single-Platform Integration：Avoid workflow friction caused by fragmented, standalone AI software by adopting a unified platform that connects directly into existing PACS/RIS.
• Flexible Computing Architecture (Edge + AWS Cloud)：Dynamically allocate workloads between local devices and AWS cloud computing during peak image volume periods.

II. Key Benefits

• 20+ Commercial AI Models in One Portfolio：Features TFDA/FDA-cleared models covering Brain (CT/MRI), Chest (LDCT/X-ray), Heart, Abdomen (Pancreas), and Breast (Mammo).
• Deep Workflow Integration：Embedded with automated report generation, lesion segmentation, worklist prioritization, and urgent AI Notifications.
• AWS Cloud Scalability & GPU Optimization：Automatically optimizes GPU resource distribution, allowing community hospitals to leverage enterprise cloud power without local server hardware.
• Operational Budget Maximization：Delivered under an AI-as-a-Service (AIaaS) subscription model, perfectly suited for the 70% OpEx quota under the Deep Cultivation Plan.

III. Pain Points Addressed

IV. Application Scenarios

• Radiology Reading Room Workflow：Automatically incorporates AI pre-screening findings (e.g., PANCREASaver® or lung nodule detection) directly into SoliPACS® Viewer and RIS reporting templates.
• Emergency Room AI Priority Alerts (AI Notify)：Real-time background AI processing triggers immediate positive warning alerts to emergency medical staff for critical cases.
• Cloud-Based Multi-Center AI Validation：Enables hospitals to evaluate advanced AI models (e.g., early pancreatic cancer detection) over AWS cloud without requiring local hardware installation.
• High Maintenance of Multiple AI Vendors：Functions as an enterprise Carrier, connecting various AI algorithms into existing PACS/RIS with a single point of integration and support.
• Delayed Critical Care in ER：AI Notify runs background inferences on X-rays and instantly alerts ER clinicians to high-risk conditions like pneumothorax.

EBM AI Platform x Acer Medical — (VeriSee & VeriOsteo AI Suite)

EBM x Acer — Specialties：Radiology

I. Hospital Needs

• Expanding Multi-Specialty Early Screening：In line with the Deep Cultivation Plan and chronic disease control policies, hospitals need to enhance early screening for diabetic eye complications and age-related osteoporosis.
• Maximizing Clinical Value via Opportunistic Screening：Hospitals seek to leverage routine diagnostic exams (such as standard Chest X-rays) to discover hidden health risks without added radiation or patient cost.

II. Key Benefits

• 4-in-1 TFDA-Cleared AI Model Portfolio：Integrates 3 fundus AI tools—VeriSee DR (Diabetic Retinopathy), VeriSee GLC (Glaucoma), and VeriSee AMD (Age-related Macular Degeneration)—plus VeriOsteo OP (Chest X-ray Osteoporosis Screening).
• Seamless Workflow Integration：Directly connects with EBM AI Platform and SoliPACS, automatically generating PDF reports without altering physicians' daily reading habits.
• Opportunistic CXR Osteoporosis Screening：VeriOsteo OP estimates T-scores directly from routine chest X-rays, enabling early risk stratification without needing expensive DEXA hardware.

III. Pain Points Addressed

IV. Application Scenarios

• Diabetes Care Centers & Endocrinology Outpatient：Enables automated, instant retinal lesion analysis (DR, GLC, AMD) during annual eye checkups for diabetic patients.
• Health Examination & Radiology Departments：Automatically runs VeriOsteo OP on routine chest X-rays to generate T-score estimates and flag silent low bone mass before fractures occur.
• Outpatient Consultation & Community Screening：Auto-generates clean, patient-friendly PDF reports for immediate doctor-patient communication and rapid follow-up referrals.