1. Genomics
Big Data Wearable/
Smart Device
Medical Informatics
Genome Sequencing
Data Science
Quantified Self
Health Avatar

2. Wearable and Medicine

4. Emergency!!

9. Heart Monitor of AliveCor

11. SAMSUNG Gear

13. Evolution of Diabetes Control
Insulin
Glucose
Insulin
Injection
Episodic
Glucose
Monitoring
Continuous
Insulin
Injection
Continuous
Glucose
Monitoring
Artificial
Pancreas

14. Google’s
Smart Contact Lenses
Glucose Monitoring

16. Smart/Mobile Healthcare

20. KDNP 당뇨병수첩 – NFC 기반 혈당 결과 무선 전송 기능 포함

28. Date Calorie Budget Calories Logged Breakfast Cals Lunch Cals Dinner Cals. % Red % Yellow % Green
2014-05-23 1,400 1,325 386 463 476 29.00% 70.00% 0.00%
2014-05-22 1,400 1,672 238 566 868 28.00% 71.00% 0.00%
2014-05-19 1,400 196 196 0 0 0.00% 100.00% 0.00%
2014-05-17 1,400 695 283 412 0 0.00% 100.00% 0.00%
2014-04-05 1,400 477 477 0 0 0.00% 0.00% 100.00%
2014-03-22 1,400 576 208 368 0 36.00% 0.00% 63.00%
2013-12-15 1,400 800 300 200 300 37.00% 62.00% 0.00%
2013-08-14 1,400 665 0 0 665 0.00% 54.00% 45.00%
2013-08-10 1,400 150 0 150 0 0.00% 100.00% 0.00%
2013-08-09 1,400 440 440 0 0 54.00% 0.00% 45.00%
2013-07-05 1,400 200 200 0 0 0.00% 100.00% 0.00%

46. 애니팡 성공 – SNS 경쟁

47. Apple Healthbook

50. Genomics/
Biomarker
Big Data/
Medical Informatics
Smart Device/
Wearable
Genome Sequencing
Data Science
Quantified Self
Health Avatar
Mobile Health
Machine Learning

52. Diabetic patients
(n = 12,074; 35,545 fundus
examinations)
The time from onset of retinopathy to clinical diagnosis of diabetes
was calculated as a point estimate by extrapolating the intercept of
the best-fitting regression line with the horizontal axis.
2014 DC Estimating the Delay Between Onset and Diagnosis of Type 2 Diabetes From the Time Course of Retinopathy Prevalence

53. 2014 DC Estimating the Delay Between Onset and Diagnosis of Type 2 Diabetes From the Time Course of Retinopathy Prevalence

54. 의료 정보학
Medical Informatics
• 처방전달 시스템(OCS)
• 영상정보 저장전달 시스템(PACS)
• 전자의무기록(EMR)
• 의료 빅데이터
• 인공지능

62. 빅 데이터 분석
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
1/Creatinine
한 환자의 10년간 신장기능의 변화 전체 환자의 당 조절 정도 분포

63. AFTER
• Dialysis pts, Hb <11 g/dL
• Non-dialytic CKD
eGFR <30 mL/min/1.73m2
Hb <10 g/dL
BEFORE
• Dialysis pts, Hb <11
g/dL
- 6m 0m 6m 12m
Reimbursement
change
(pint/person-year)
Transfusion requirement

64. …………………….

65. Medical Big Data

67. Big data platform model by Korea Institute
of Drug Safety and Risk Management

68. Future drug safety monitoring
system based on the big data

69. Overview of secondary data in
public health by data source

70. Medical Big Data

71. Medical Big Data

72. Anti-hypertensive
prescriptions
(2008-2011)
N = 8,315,709
New users
N = 2,357,908
Age ≥ 50 yrs
Monotherapy
Compliant user (MPR≥80%)
No previous fracture
N = 528,522
Prevalent users
N = 5,957,801
Excluded
Age <50
Combination therapy
Inadequate compliance
Previous fracture
N = 1,829,386
Final study population
심평원 빅데이터 연구
고혈압약과 골절
Choi et al., in revision

73. Fracture rates per 10,000 person-years (95% CI)
819
Fracture Rates
(per 10,000 Person-Years)
Total
Male
Female
AB: alpha-adrenergic blocker
ACEI: angiotensin converting enzyme inhibitor
DIUR: diuretics
CCB: calcium channel blocker
BB: beta-adrenergic blocker
ARB: angiotesin-receptor blocker

74. 2008-2011 Prescriptions
N = 2,886,555
New Users
N = 718,293
Monotherapy+Combination (MPR>80%)
Age > 50 yrs
No previous fracture
N = 208,648
심평원 빅데이터 연구
당뇨병약과 골절

75. Total
0 200 400 600
Metformin+DPP4i
SU+TZD
Metformin+TZD
Metformin+SU
AGI
SU
Metformin
Non-user
Fracture Rates per 10,000 Person-Years
Female
0 200 400 600
Metformin+DPP4i
SU+TZD
Metformin+TZD
Metformin+SU
AGI
SU
Metformin
Non-user
Fracture Rates per 10,000 Person-Years
Fracture Rates
(per 10,000 Person-Years)
0 200 400 600
Metformin+DPP4i
SU+TZD
Fracture Rates per 10,000 Person-Years
Male
0 200 400 600
Metformin+DPP4i
SU+TZD
Metformin+TZD
Metformin+SU
AGI
SU
Metformin
Non-user
Fracture Rates per 10,000 Person-Years
Total
Male
Female

76. Medical Big Data
 Artificial Intelligence

77. Jeopardy!
2011년 인간 챔피언 두 명 과 퀴즈 대결을 벌여서 압도적인 우승을 차지

78. Medical Big Data
 Artificial Intelligence

82. 2013 PLOS CB Reassessing Google Flu Trends Data for Detection of Seasonal and Pandemic Influenza
Google Flu Trends

83. Social Network and
Obesity Prevalence
2013 PLOS One. Assessing the Online Social Environment for Surveillance of Obesity Prevalence

86. 2014 JAMA Finding the Missing Link for Big Biomedical Data

88. Genomics
Big Data Wearable/
Smart Device
Medical Informatics
Genome Sequencing
Data Science
Quantified Self
Health Avatar

89. http://www.yoonsupchoi.com

90. Any Questions?
• 최형진
• Hyung Jin Choi
• hjchoimd@gmail.com
• www.facebook.com/hyungjin.choi.75