Chin-Chung Tseng Taiwan

19th September 2026 Saturday

Time Session
14:00
15:30
Chia-Chao Wu Moderator
Chin-Chung Tseng Moderator
  • Chia-Chao Wu Speaker
  • Sejoong Kim Speaker Korean Big-Data Experience in AKI and CRRT OutcomesSouth Korea has established a robust nationwide health data infrastructure, enabling large-scale analyses of acute kidney injury (AKI) and continuous renal replacement therapy (CRRT). Leveraging the Health Insurance Review and Assessment Service (HIRA) and National Health Insurance Service (NHIS) databases, Korean researchers have characterized AKI incidence, risk factors, and short- and long-term outcomes across diverse clinical settings. Studies utilizing CRRT data have identified predictors of mortality, renal recovery, and progression to chronic kidney disease. These big-data approaches provide critical real-world evidence, informing clinical practice and guiding future interventional strategies in critically ill patients with AKI.Precision Volume Management in CRRT: Insights from Bioimpedance and BiomarkersOptimal fluid balance is critical in critically ill patients undergoing continuous renal replacement therapy (CRRT), yet accurate volume assessment remains challenging. Bioimpedance analysis (BIA) offers a non-invasive, objective method to quantify fluid overload and guide individualized ultrafiltration targets. Complementing BIA, emerging biomarkers provide dynamic, real-time insights into volume status and end-organ perfusion. Integrating these tools into a precision medicine framework may optimize fluid removal strategies, reduce complications, and improve survival outcomes in CRRT-dependent patients. Prospective validation of this combined approach is warranted.
  • Chin Lin Speaker Deep Learning Electrocardiography as a Non-Invasive Window into Kidney Function and Electrolyte DisturbancesRecent advances in deep learning have transformed the standard 12-lead electrocardiogram (ECG) from a tool for rhythm interpretation into a scalable physiologic sensor capable of detecting systemic disease. In this lecture, we will review the development and clinical translation of AI-enabled ECG models for dyskalemia detection and renal-function estimation. Using large real-world cohorts, convolutional and attention-based neural networks have demonstrated high accuracy for identifying moderate-to-severe hyperkalemia and hypokalemia directly from ECG waveforms, frequently preceding laboratory confirmation and outperforming clinician interpretation. Beyond electrolyte detection, AI-ECG signatures were also associated with adverse outcomes, cardiovascular risk, and future chronic kidney disease progression, even among patients with apparently normal laboratory findings. We will further discuss pragmatic deployment studies showing how real-time AI-ECG alerts integrated into emergency department workflows can accelerate treatment decisions for life-threatening hyperkalemia. Finally, the talk will address how signal-based AI can complement EHR-based prediction models in critical-care nephrology, including issues of interpretability, calibration drift, implementation, and multimodal foundation-model integration.
  • Kianoush Kashani Speaker Practical Steps to Train (and Become) an AI-Era PhysicianAI in Critical Care Nephrology — State of the Art and the Path from Algorithm to BedsideLate breaking clinical trials or Critical Care Nephrology: Literature Review AI in the ICU or Chat GPT Applications in Critical Care Nephrology
  • Nattachai Srisawat Speaker Precision Sepsis-AKI — Biomarkers, AI and Phenotyping in the Asia-PacificTiming of DialysisAcute PD vs Acute HD: Which Is the Right Choice?
  • Chin Lin Speaker Deep Learning Electrocardiography as a Non-Invasive Window into Kidney Function and Electrolyte DisturbancesRecent advances in deep learning have transformed the standard 12-lead electrocardiogram (ECG) from a tool for rhythm interpretation into a scalable physiologic sensor capable of detecting systemic disease. In this lecture, we will review the development and clinical translation of AI-enabled ECG models for dyskalemia detection and renal-function estimation. Using large real-world cohorts, convolutional and attention-based neural networks have demonstrated high accuracy for identifying moderate-to-severe hyperkalemia and hypokalemia directly from ECG waveforms, frequently preceding laboratory confirmation and outperforming clinician interpretation. Beyond electrolyte detection, AI-ECG signatures were also associated with adverse outcomes, cardiovascular risk, and future chronic kidney disease progression, even among patients with apparently normal laboratory findings. We will further discuss pragmatic deployment studies showing how real-time AI-ECG alerts integrated into emergency department workflows can accelerate treatment decisions for life-threatening hyperkalemia. Finally, the talk will address how signal-based AI can complement EHR-based prediction models in critical-care nephrology, including issues of interpretability, calibration drift, implementation, and multimodal foundation-model integration.
    Kianoush Kashani Speaker Practical Steps to Train (and Become) an AI-Era PhysicianAI in Critical Care Nephrology — State of the Art and the Path from Algorithm to BedsideLate breaking clinical trials or Critical Care Nephrology: Literature Review AI in the ICU or Chat GPT Applications in Critical Care Nephrology
    Nattachai Srisawat Speaker Precision Sepsis-AKI — Biomarkers, AI and Phenotyping in the Asia-PacificTiming of DialysisAcute PD vs Acute HD: Which Is the Right Choice?
    Sejoong Kim Speaker Korean Big-Data Experience in AKI and CRRT OutcomesSouth Korea has established a robust nationwide health data infrastructure, enabling large-scale analyses of acute kidney injury (AKI) and continuous renal replacement therapy (CRRT). Leveraging the Health Insurance Review and Assessment Service (HIRA) and National Health Insurance Service (NHIS) databases, Korean researchers have characterized AKI incidence, risk factors, and short- and long-term outcomes across diverse clinical settings. Studies utilizing CRRT data have identified predictors of mortality, renal recovery, and progression to chronic kidney disease. These big-data approaches provide critical real-world evidence, informing clinical practice and guiding future interventional strategies in critically ill patients with AKI.Precision Volume Management in CRRT: Insights from Bioimpedance and BiomarkersOptimal fluid balance is critical in critically ill patients undergoing continuous renal replacement therapy (CRRT), yet accurate volume assessment remains challenging. Bioimpedance analysis (BIA) offers a non-invasive, objective method to quantify fluid overload and guide individualized ultrafiltration targets. Complementing BIA, emerging biomarkers provide dynamic, real-time insights into volume status and end-organ perfusion. Integrating these tools into a precision medicine framework may optimize fluid removal strategies, reduce complications, and improve survival outcomes in CRRT-dependent patients. Prospective validation of this combined approach is warranted.
  • Chia-Chao Wu Speaker
Room 5