Department Introduction
Major Milestones
Time LineReceived two 3-year NSTC grants for cardiology and nephrology research
Signed MOU and NDA and initiated AI projects with the world’s first AI university – Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi
Collaborated with Ever Fortune. AI Co. to develop an intelligent cardiothoracic ratio estimation system, which the US FDA (K212624) and Taiwan TFDA (007443) approved as a software as a medical device
Accumulated nearly 80 international journal publications, with at least 20 papers in high-impact journals (IF>10 or 10% of the field)
Accumulated 1 US and 3 Taiwan patents (I746249, I755108, I768288) for data and AI intelligence tools
Received Catalyst Award of 2023 Healthy Longevity Grand Challenge Competition for "Deep Kidney Aging Clock" granted by US National Academy of Medicine and Academia Sinica
Received Silver Award of the National Healthcare Quality Award (NHQA) for "iHi Platform"
Received 19th National Innovation Award for " iHi Platform" and was selected as top 7 for pitch demo
Promoted the business contract between Ever Fortune. AI Co. and a dialysis device company in Singapore that worth 38 million USD
Collaborated with BPM Co. to investigate the novel biomarker for acute kidney injury and presented in European Renal Association 2022
Established “iHi Genomics” analytic platform that integrated genotype data and clinical phenotypes from 230,000 patients
As the first medical center to acquire ISO 29100 & 29191 and CNS 29100-2 for medical data de-identification
Preoperative blood glucose and hospital stay days study published in Diabetes Care (IF 19.112)
Collaborated with Asia University to receive 4-year grant from National Science and Technology Council (NSTC) grant of "Cross-Domain Development and Value-Added Applications of Clinical Databases and AI " for the "Strong Kidney Initiative" project
Signed NDA with a dialysis device company in Singapore
Launched iHi Platform that includes deep-cleaned, integrated, and diverse e-medical records and environmental data from 3 million patients with 19-year follow-up
Predictive intelligence for chronic kidney disease by renal ultrasound published in Nature Digital Medicine (IF 15.537)
Created a high-resolution nationwide PM2.5 exposure map and linked with EMR
Received BDC’s first Taiwan patent for Acute Kidney Injury Detection System
Special Reports "Application of Artificial Intelligence in Predicting Dialysis " on CTI News by CTI Television Inc. (reported on 2019.03.10)
AI Cover Story Series on Business Today Magazine (Vol. 1153; published on 2019.01.28)
Deputy Director Chin-Chi Kuo presented "Big Data and Their Clinical Applications: Core Concepts and Updates" at Taipei Veterans General Hospital
Big Data Center was video-highlighted in "2018 Kidney Week", the only research center in Asia
The Big Data Center of CMUH holds the high-quality medical data, including structured and unstructured data, and is capable to expend the value of these data by integratingit to the universal Taiwan’s National Health Insurance Database, the government-based registry data,and the environmental data.With these high dimensional and high-quality data, we can extract and generate real-world evidence for clinical practice and health policy-making.
Take the renal medicine at CMUH as examples. Wenow can use the serial repeated measurement ofeGFR to track the disease course and predict patients’ risk of developing adverse outcomes for each patient who received care at our hospital.
One example is the CKD Vigilant Information System. We found the first year eGFR variability is very useful in predicting the disease progression, CVD, and mortality for patients receiving CKD care in our hospital. Wedevelop a real-time automated risk alarming system to help nephrologist’s everyday practice.
Another example is the Acute Kidney Injury Detection System (AKIDS). We link our on-sitedata with the on-cloud national datatoobtain the complete health information. Then we develop a detection algorithm to screen forAKI and make referral recommendation for every outpatient in our hospital.Our system can also help identify the window for clinicians to avoid nephrotoxic agents in patients with AKI.