• Hospitalized or emergency department patients

• All ward patients

• High-risk mortality patients

• Rural area residents (88 service points)

Developed a proprietary AI-enabled electrocardiographic (ECG) mortality prediction model integrated with clinical trial validation. The AI alert system predicts patient mortality risk within 90 days, enabling physicians to perform early intervention and intensive care, demonstrating significant improvement in patient survival rates.

• AI-ECG accuracy of 0.93-0.96, superior to international standards

• World's first clinical trial validating AI-ECG mortality reduction

• Overall mortality reduction of 17%, high-risk patient mortality reduction of 31%

• Cardiac mortality reduction of 93%

• Cost-effectiveness of 99.6%

• Approved by Taiwan FDA as medical device

• Published in Nature Medicine with impact factor 58.7

• Clinical trial sample: 16,335 patients (AI alert intervention group 8,177, routine care group 8,158)

• High mortality risk patients: 709 (8.9%)

• Rural area ECG interpretation volume: over 29,000 cases

• Hospital coverage: 415 attending physicians, 1,949 nurses, 780 administrative staff, 707 other healthcare professionals, 776 physicians

• All-cause mortality reduction of 17% within 90 days

• High-risk patient mortality reduction of 31%

• Cardiac mortality reduction of 93%

• Non-cardiac mortality reduction of 24%

• Increased ICU admission rate, antiarrhythmic drug use, echocardiography rate with physician intervention

• AI prediction accuracy: internal validation 0.93-0.96, external validation 0.88

• Can detect 29 acute and chronic cardiovascular diseases, interpret 24 arrhythmia conditions

• AI mortality risk prediction accuracy of 99%

• Randomized clinical trial design ensures scientific rigor

• Dual validation mechanism with internal data validation and external data verification

• Approved by Taiwan FDA as medical device

• Regular monitoring of AI model accuracy indicators by team

• High physician acceptance of AI alert system as clinical reference

• Early prognostic notification improves clinical decision-making confidence

• Multiple medical centers actively adopting the system (Fuhsing Hospital, Far Eastern Memorial Hospital, etc.)

• Published in Nature Medicine (impact factor 58.7, ranked first in medical research, out of 189 journals)

• Published over 30 SCI international papers

• Recognized and reported by American Heart Association

• International multi-center validation collaboration: Cedars-Sinai Medical Center Los Angeles, Mount Sinai Center New York, Seoul National University Hospital, Oxford University Hospital

• 2022 Future Technology Award

• 2023 Taipei Biotech Award - Cross-domain Excellence Category Gold Award

• 2023 MediaTek Smart Hometown Competition Excellent Award

• Cost-effectiveness analysis of 5000 cases: 99.6% probability of cost-effectiveness with AI-ECG intervention

• Reduces in-hospital cardiovascular mortality events

• Improves patient outcomes, enables early detection of potential cardiac diseases

• Enhances physician clinical decision support

• Advances Taiwan's smart healthcare development

• Benchmark learning and multi-center verification domestically and internationally

• Technology transfer collaboration with Quanta Services in 2023