NCKU Introduces Smart Healthcare, Raises Efficiency of Clinical Inspection of the Novel Coronavirus
The second part integrates research results from the NCKU AI Innovation Research Center and the Capstone Plan into the capacity of NCKU smart healthcare to automate medical records. Traditional pen-and-paper inputting of data or orally inquiring of the patient's medical history both increase the infection risk of medical personnel due to proximity with patients. Automating medical records allows personnel to enter medical data such as travel history, work history, contact history, and group history into a tablet and upload them to the medical record system. The personnel can then instantly receive relevant data to make a clinical decision. Tablets are disinfected with rubbing alcohol after each use, reducing the risk of cross-infection and raising efficiency of inspection.
Since the threat of the recent viral proliferation began, NCKU and NCKU Hospital have mobilize healthcare professionals in the fight against the virus
The third part introduces AI-assisted detection of inflammation in the lungs. The AI-assisted system for reading chest radiographs to find inflammation in the lungs was developed by the AI team and information team of NCKU Hospital. The hospital's inflammation image data is also incorporated in the system. Currently, the data has been used to assist in the screening of 152 images suspected of presenting the novel coronavirus. The system can provide a sensitivity and accuracy of as high as 80% and 90%, respectively.
The three-part inspection system also incorporates the latest epidemiological developments provided daily by the CDC, such as expansion of quarantined areas. The result is the Smart Healthcare Clinical Decision Support System, which is built into the inspection station computer system, where it relieves some of the personnel's pressure in making clinical decisions when responding to the virus. The entire process—from entering the station to the doctor's decision of whether to report for hospital quarantine or at-home inspection—is shortened from 2.5 hours to just 30 minutes.
Monitoring and prediction are a very important part of the process of preventing the further spread of the virus. Thus, the interdisciplinary team at NCKU and tech company AMobile Intelligent have collaborated in the development of the smart-monitoring wristband. The wristband can continuously monitor the wearer's body temperature and heart rate; before a fever occurs, a rise will manifest in the wearer's shell temperature, which will be detected by the wristband and the wearer can be alerted of the coming fever. Closely monitoring the trend of changes in body temperature and providing timely alerts for abnormalities, the wristband can alert the wearer to take early and appropriate action. Currently, 130 healthcare personnel at NCKU Hospital have volunteered to wear the wristbands. NCKU students who are under at-home quarantine and suspected cases of coronavirus and their families have also donned the wristbands for continuous monitoring of body temperature.
The interdisciplinary team at NCKU uses a "smart-monitoring wristband" to help implement at-home quarantine policy
Responding to this pandemic, the NCKU Hospital, the College of Medicine, College of Electrical Engineering and Computer Science, College of Sciences, and School of Management have formed an interdisciplinary, cross-departmental, cross-group team which incorporates medical resources and uses science and professional knowledge in the fight against the virus. The automated medical record system was developed by an information engineering team led by Clinical Medicine Research Center director Ping-Yen Liu, and is a seamless system created from their experience with the automated precision medical record system over the past year.
The model of the AI-assisted system for reading chest radiographs for lung inflammation was developed by the information team under the leadership of Tsai Yi-Shan of the Department of Radiology at NCKU Hospital, with active assistance from the team headed by professor Sun Yong-Nian of the College of Electrical Engineering and Computer Science. The teams used the advanced AI-automated chest radiograph reading model for pulmonary tuberculosis developed at the AI Innovation Research Center, to which they incorporated images of lung inflammation from the NCKU Hospital. With the two used in tandem, the overall speed of the reading is maximized.
NCKU brings together several smart healthcare methods in its "Smart Healthcare Clinical Decision Support System"
The smart-monitoring wristband was developed with the support of the Department of Foresight and Innovation Policies under the MOST along with Ke Nai-Ying, head of the Department of Nursing; Ko Wen-Chien, deputy superintendent of NCKU Hospital; Chen Po-Lin, head of the Center for Disease Control; Chuang Kun-Ta, assistant professor of the Department of Computer Science and Information Engineering; Kao Hung-Yu, dean of the Department of Computer Science and Information Engineering; and Yu-Chen Shu, assistant professor of the Department of Mathematics; as well as collaborating technology companies.
(Text by Zhang Yi-Ting; Photos by Zhang Yi-Ting and Liu Zi-You)
Provider: News Center