Feature Article: Smart Healthcare Emergency Department Return Prediction System Using Blood Samples With LightGBM for Smart Health Care Services Younghwan Shin Yonsei University Sangdo Kim Yonsei University Jong-Moon Chung Yonsei University Hyun Soo Chung Yonsei University Severance Hospital Sang Gil Han Yonsei University Yongin Severance Hospital Junho Cho Yonsei University Severance Hospital Abstract-This article proposes a novel Blood sample-based Emergency department (ED) Return (BER) scheme that predicts the ED return probability using LightGBM. In the proposed BER scheme, LightGBMmakes predictions on ED return based on blood samples. Since blood sample analysis is one of themost commonmedical procedures, the proposed scheme can help to improve ED patient care for hospitals. The proposed BER smart health care system and internet of medical things (IoMT) blockchain network was tested from the ED of the Severance Hospital of Yonsei University, located in Seoul of SouthKorea. The results show that the proposed BER scheme is superior in predicting ED return visits based on achieving a higher Area Under the Curve of the Receiver Operating Characteristic performance, alongwith the advantage of usingmuch lesser data and being faster. Digital Object Identifier 10.1109/MCE.2020.3015439 Date ofpublication 11 August 2020; date ofcurrent version 13 April 2021. 42 2162-2248 ß 2020 IEEE Published by the IEEE Consumer Technology Society IEEE Consumer Electronics Magazine