Most people are now familiar with the concepts of big data, deep learning, machine learning, and artificial intelligence (AI) and have a vague expectation that AI using medical big data can be used to improve the quality of medical care. However, the expectation that big data could change the field of medicine is inconsistent with the current reality. The clinical meaningfulness of the results of research using medical big data needs to be examined. Medical staff needs to be clear about the purpose of AI that utilizes medical big data and to focus on the quality of this data, rather than the quantity. Further, medical professionals should understand the necessary precautions for using medical big data, as well as its advantages. No doubt that someday, medical big data will play an essential role in healthcare; however, at present, it seems too early to actively use it in clinical practice. The field continues to work toward developing medical big data and making it appropriate for healthcare. Researchers should continue to engage in empirical research to ensure that appropriate processes are in place to empirically evaluate the results of its use in healthcare.

Citations

Citations to this article as recorded by  

• Long-Term Risk of Cardiovascular Disease Among Type 2 Diabetes Patients According to Average and Visit-to-Visit Variations of HbA1c Levels During the First 3 Years of Diabetes Diagnosis
  Hyunah Kim, Da Young Jung, Seung-Hwan Lee, Jae-Hyoung Cho, Hyeon Woo Yim, Hun-Sung Kim
  Journal of Korean Medical Science.2023;[Epub]     CrossRef
• Angiotensin‐converting enzyme inhibitors versus angiotensin receptor blockers: New‐onset diabetes mellitus stratified by statin use
  Juyoung Shin, Hyunah Kim, Hyeon Woo Yim, Ju Han Kim, Suehyun Lee, Hun‐Sung Kim
  Journal of Clinical Pharmacy and Therapeutics.2022; 47(1): 97.     CrossRef
• Physician Knowledge Base: Clinical Decision Support Systems
  Sira Kim, Eung-Hee Kim, Hun-Sung Kim
  Yonsei Medical Journal.2022; 63(1): 8.     CrossRef
• Sodium-Glucose Cotransporter-2 Inhibitor-Related Diabetic Ketoacidosis: Accuracy Verification of Operational Definition
  Dong Yoon Kang, Hyunah Kim, SooJeong Ko, HyungMin Kim, Jiwon Shinn, Min-Gyu Kang, Sun-ju Byeon, Jeong-Hee Choi, Soo-Yong Shin, Hun-Sung Kim
  Journal of Korean Medical Science.2022;[Epub]     CrossRef
• Drug Repositioning: Exploring New Indications for Existing Drug-Disease Relationships
  Hun-Sung Kim
  Endocrinology and Metabolism.2022; 37(1): 62.     CrossRef
• A Study on Methodologies of Drug Repositioning Using Biomedical Big Data: A Focus on Diabetes Mellitus
  Suehyun Lee, Seongwoo Jeon, Hun-Sung Kim
  Endocrinology and Metabolism.2022; 37(2): 195.     CrossRef
• Development of a predictive model for the side effects of liraglutide
  Jiyoung Min, Jiwon Shinn, Hun-Sung Kim
  Cardiovascular Prevention and Pharmacotherapy.2022; 4(2): 87.     CrossRef
• Understanding and Utilizing Claim Data from the Korean National Health Insurance Service (NHIS) and Health Insurance Review & Assessment (HIRA) Database for Research
  Dae-Sung Kyoung, Hun-Sung Kim
  Journal of Lipid and Atherosclerosis.2022; 11(2): 103.     CrossRef
• The Impact of the Association between Cancer and Diabetes Mellitus on Mortality
  Sung-Soo Kim, Hun-Sung Kim
  Journal of Personalized Medicine.2022; 12(7): 1099.     CrossRef
• Development of Various Diabetes Prediction Models Using Machine Learning Techniques
  Juyoung Shin, Jaewon Kim, Chanjung Lee, Joon Young Yoon, Seyeon Kim, Seungjae Song, Hun-Sung Kim
  Diabetes & Metabolism Journal.2022; 46(4): 650.     CrossRef
• Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes
  Han-sang Baek, Ji-Yeon Park, Jin Yu, Joonyub Lee, Yeoree Yang, Jeonghoon Ha, Seung Hwan Lee, Jae Hyoung Cho, Dong-Jun Lim, Hun-Sung Kim
  Endocrinology and Metabolism.2022; 37(4): 641.     CrossRef
• Retrospective cohort analysis comparing changes in blood glucose level and body composition according to changes in thyroid‐stimulating hormone level
  Hyunah Kim, Da Young Jung, Seung‐Hwan Lee, Jae‐Hyoung Cho, Hyeon Woo Yim, Hun‐Sung Kim
  Journal of Diabetes.2022; 14(9): 620.     CrossRef
• Long-Term Changes in HbA1c According to Blood Glucose Control Status During the First 3 Months After Visiting a Tertiary University Hospital
  Hyunah Kim, Da Young Jung, Seung-Hwan Lee, Jae-Hyoung Cho, Hyeon Woo Yim, Hun-Sung Kim
  Journal of Korean Medical Science.2022;[Epub]     CrossRef
• Medication based machine learning to identify subpopulations of pediatric hemodialysis patients in an electronic health record database
  Autumn M. McKnite, Kathleen M. Job, Raoul Nelson, Catherine M.T. Sherwin, Kevin M. Watt, Simon C. Brewer
  Informatics in Medicine Unlocked.2022; 34: 101104.     CrossRef
• Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness
  Juyoung Shin, Joonyub Lee, Taehoon Ko, Kanghyuck Lee, Yera Choi, Hun-Sung Kim
  Journal of Personalized Medicine.2022; 12(11): 1899.     CrossRef
• A Study on Weight Loss Cause as per the Side Effect of Liraglutide
  Jin Yu, Jeongmin Lee, Seung-Hwan Lee, Jae-Hyung Cho, Hun-Sung Kim, Heng Zhou
  Cardiovascular Therapeutics.2022; 2022: 1.     CrossRef
• Risk Classification and Subphenotyping of Acute Kidney Injury: Concepts and Methodologies
  Javier A. Neyra, Jin Chen, Sean M. Bagshaw, Jay L. Koyner
  Seminars in Nephrology.2022; 42(3): 151285.     CrossRef
• Estimation of sodium‐glucose cotransporter 2 inhibitor–related genital and urinary tract infections via electronic medical record–based common data model
  SooJeong Ko, HyungMin Kim, Jiwon Shinn, Sun‐ju Byeon, Jeong‐Hee Choi, Hun‐Sung Kim
  Journal of Clinical Pharmacy and Therapeutics.2021; 46(4): 975.     CrossRef
• Blood glucose levels and bodyweight change after dapagliflozin administration
  Hyunah Kim, Seung‐Hwan Lee, Hyunyong Lee, Hyeon Woo Yim, Jae‐Hyoung Cho, Kun‐Ho Yoon, Hun‐Sung Kim
  Journal of Diabetes Investigation.2021; 12(9): 1594.     CrossRef
• Artificial intelligence in healthcare: possibilities of patent protection
  T. N. Erivantseva, Yu. V. Blokhina
  FARMAKOEKONOMIKA. Modern Pharmacoeconomic and Pharmacoepidemiology.2021; 14(2): 270.     CrossRef
• Lack of Acceptance of Digital Healthcare in the Medical Market: Addressing Old Problems Raised by Various Clinical Professionals and Developing Possible Solutions
  Jong Il Park, Hwa Young Lee, Hyunah Kim, Jisan Lee, Jiwon Shinn, Hun-Sung Kim
  Journal of Korean Medical Science.2021;[Epub]     CrossRef
• Prospect of Artificial Intelligence Based on Electronic Medical Records
  Suehyun Lee, Hun-Sung Kim
  Journal of Lipid and Atherosclerosis.2021; 10(3): 282.     CrossRef
• Data Pseudonymization in a Range That Does Not Affect Data Quality: Correlation with the Degree of Participation of Clinicians
  Soo-Yong Shin, Hun-Sung Kim
  Journal of Korean Medical Science.2021;[Epub]     CrossRef
• Development of a Predictive Model for Glycated Hemoglobin Values and Analysis of the Factors Affecting It
  HyeongKyu Park, Da Young Lee, So young Park, Jiyoung Min, Jiwon Shinn, Dae Ho Lee, Soon Hyo Kwon, Hun-Sung Kim, Nan Hee Kim
  Cardiovascular Prevention and Pharmacotherapy.2021; 3(4): 106.     CrossRef
• Modeling of Changes in Creatine Kinase after HMG-CoA Reductase Inhibitor Prescription
  Hun-Sung Kim, Jiyoung Min, Jiwon Shinn, Oak-Kee Hong, Jang-Won Son, Seong-Su Lee, Sung-Rae Kim, Soon Jib Yoo
  Cardiovascular Prevention and Pharmacotherapy.2021; 3(4): 115.     CrossRef
• TRAINING IN BIG DATA TECHNOLOGIES OF MEDICAL UNIVERSITY STUDENTS
  K.S ITINSON
  AZIMUTH OF SCIENTIFIC RESEARCH: PEDAGOGY AND PSYCHOLOGY.2021;[Epub]     CrossRef
• Machine Learning Applications in Endocrinology and Metabolism Research: An Overview
  Namki Hong, Heajeong Park, Yumie Rhee
  Endocrinology and Metabolism.2020; 35(1): 71.     CrossRef
• Lessons from Use of Continuous Glucose Monitoring Systems in Digital Healthcare
  Hun-Sung Kim, Kun-Ho Yoon
  Endocrinology and Metabolism.2020; 35(3): 541.     CrossRef
• Apprehensions about Excessive Belief in Digital Therapeutics: Points of Concern Excluding Merits
  Hun-Sung Kim
  Journal of Korean Medical Science.2020;[Epub]     CrossRef
• Medical Ethics in the Era of Artificial Intelligence Based on Medical Big Data
  Hae-Ran Na, Hun-Sung Kim
  The Journal of Korean Diabetes.2020; 21(3): 126.     CrossRef
• Machine Learning Application in Diabetes and Endocrine Disorders
  Namki Hong, Heajeong Park, Yumie Rhee
  The Journal of Korean Diabetes.2020; 21(3): 130.     CrossRef
• Real World Data and Artificial Intelligence in Diabetology
  Kwang Joon Kim
  The Journal of Korean Diabetes.2020; 21(3): 140.     CrossRef