20160119 디지털 헬스케어 의사모임 1월 전체 파일 v3

디지털 헬스케어의사모임 1월 모임 발표자료

2016.1.19

디지털 헬스케어업데이트

김치원

2016.1.19

IBM Watson + Medtronic: CGM을 통한 저혈당 예측 알고리즘

• CES 2016에서 발표

• Medtronic과 IBM 왓슨의 협

업으로 지속형 혈당 측정계를

사용해서 저혈당 발생을 최대 3

시간 전에 예측할 수 있는 알고

리즘을 개발했다고 발표

• 당뇨병 관리 서비스를 출시할

예정이라고 발표

활동량 측정계의 겨울 1: Fitbit, 애플워치와 유사한 신제품 출시 후주가 급락

활동량 측정계의 겨울 2: 조본, Down-round

Fitbit의 심박수 측정이 정확도에 대한 집단 소송에 제기됨

Proteus의 스마트 알약을 Barton Health System병원에서 사용

• Proteus 회사가 만든 스마트 알약 Helius는

임상 시험 용으로 발표되었고 오츠카제약의

Abilify와 결합한 상태로 FDA 승인 잘차를

밟고 있음

• 캘리포니아의 지역 병원인 Barton Health

System에서 고혈압 약물에 대해서 사용하겠

다고 발표

• 이슈

• FDA 승인은 필요 없는지?

• 병원에서 지속적으로 사용 가능할 지?

Validic: 스마트폰 카메라를 사용한 의료기기 데이터 수집

빅데이터분석:

유전체정보와개인라이프로그정보활용

서울대 최형진9

Contents

1. Introduction

2. Human Genome Project and Beyond

3. Genome Data① Cancer Targeted Therapy

② Disease Risk (Common, Rare)

③ Pharmacogenomics

④ Others (Fetal DNA, Microbiome)

4. Sensor/Mobile Data

5. Electrical Health Records

6. National Healthcare Data

7. Medical Images

8. Biomedical Big Data + Artificial Intelligence

$215MPrecision Medicine Initiative

2015/1/30

Integration of Multi-Big-Data

2013.4.25. KBS 9시뉴스

며칠 전 유전자 검사를 받은 40대 남성입니다.혈액세포의 DNA 상태를 분석해 앞으로 암에 걸릴 위험이 있는지 여부를 판단할 수있다고 합니다.

2013.4.25. KBS 9시뉴스

2013.4.25. KBS 9시뉴스

60년전 DNA의 구조가 밝혀진 이래 2003년 인간 유전자 지도가 완성됐고, 현재는 어떤유전자가 어떤 질병을 일으키는지 분석도 80% 정도 끝난 상태입니다.예를들어 13번 염색체의 BRCA2 유전자에 이상이 생기면 유방암에 걸릴 확률이높습니다. 또 17번 염색체 유전자는 난소암, 7번 염색체 유전자는 비만을 일으킵니다.

21

Heart Disorder 99% Probability

Life Expectancy 30.2 Years

Contents

1. Introduction









7. Medical Images


Promise of Human Genome Project

Tissue Specific Expression

Comprehensive Catalogues of Genomic Data

Variation in the human genome

Mendelian (monogenic) diseases (N=22,432)

Whole genome sequencing (N=1,000)

Four ethnic groups (CEU, YRI, JPT, CHB, N=270)

GWAS catalogComplex (multigenic) traits(1926 publications and 13410 SNPs)

Disease-related variations

Functional elements

2014-06-29

25

All Major Tissues/Organs

All Proteins + All RNAs

2015 Science Tissue-based map of the human proteome

1. Immunohistochemistry (IHC)24,028 antibodies (16,975 proteins) >13 million IHC images

2. RNA-sequencing

(N=44)26

111 Reference Human Epigenomes

2015.2.19. Nature. Integrative analysis of 111 reference human epigenomes

27

Data Dimensions

2015.2.19. Nature. Integrative analysis of 111 reference human epigenomes

29

Network-based Model of

Disease-disease Relationship

2015 Science Uncovering disease-disease relationships through the incomplete interactome30

Hypothesis Driven Science Data Driven Science

Hypothesis

Collect Data

Data

GenerateHypothesis

Analyze

Analyze

Candidate Gene

Approach

Genome-wide

Approach

Choose a Gene from Prior Knowledge

Analyze the Gene

Analyze ALL Genes

Discover Novel Findings

GWAS

(Genome wide association study)

SNP chipWhole Genome SNP Profiling (500K~1M SNPs)

Common Variant

Choi HJ, Doctoral Thesis

Estrada et al., Nature Genetics, 2012

+ novel targets

for bone biology

Recent largest GWAS

GEFOS consortium

2010 An Environment-Wide Association Study (EWAS) on Type 2 Diabetes Mellitus

Environment-Wide Association Study (EWAS)

다양한 환경인자들

GWAS PheWAS

Phenotype-wide Association Study

1000 개의 질병들Bioinformatics. 2010 PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

Phenotype-wide Association Study

Genome-Envirome-Phenome-wide

Association Study

Phenom

e-w

ide

(Lab, D

iagnosis

)

Proposal (Choi)

Genome-wide

Environment-wide(Life style, diet, exercise, pollution)

Anatome-Phenome-wide

Association Study

2015.2.19. Nature. Genetic and epigenetic fine mapping of causal autoimmune disease variants

Phenome

Anato

me

Contents

1. Introduction









7. Medical Images


저의유전자분석결과를반영하여

진료해주세요!! 헠?

41

What is Genomic Medicine?

Disease genetic susceptibilityCancer driver

somatic mutation

Pharmacogenomics

Targeted Cancer Treatment

(EGFR)

Causal Variant

Targeted Drug(MODY-SU)

Drug Efficacy/Side Effect Related Genotype

(CYP, HLA)

Genetic Diagnosis(Mendelian,

Cystic fibrosis)Molecular

Classification- Prognosis(Leukemia)

Hereditary Cancer(BRCA)

Microbiome(Bacteria,

Virus)

Genomic Medicine

Risk prediction(Complex disease,

Diabetes)

Germline Variants

Fetal DNA

Contents

1. Introduction









7. Medical Images


Cancer Targeted Therapy

45

Targeted TherapyGenetic TestCancer

Cancer Rebiopsy

2013 JCO Genomics-Driven Oncology- Framework for an Emerging Paradigm

Liquid Biopsy

48

Contents

1. Introduction









7. Medical Images


(출처: 금창원 대표님 블로그)

$99

TV CF

50

http://goldbio.blogspot.kr/2014/12/pg-100.html

30만원-200만원

52

GWASN=339,224 individuals97 BMI-associated loci

Tissue Specific Gene Expression

2015 Nature Genetic studies of body mass index yield new insights for obesity biology

- Hypothalamus, Pituitary gland (appetite regulation)

- Hippocampus, Limbic system (learning, cognition, emotion, memory)

Gene Set Enrichment Analysis

2015 Nature Genetic studies of body mass index yield new insights for obesity biology

Per-allele effect of BMI-associated

loci on body weight

2012 Genetic determinants of common obesity and their value in prediction

2011 Hum Genet. Type 2 diabetes and obesity- genomics and the clinic

2015 Nature Genetic studies of body mass index yield new

insights for obesity biology

Blue: Previous Red: Novel

2011 Hum Genet. Type 2 diabetes and obesity- genomics and the clinic

TCF7L2

◇◆ ‘parental obesity’ as a test to predict obesity in adult life•Dark blue 1–2 yrs •Green 3–5 yrs •Red 6–9 yrs•Light blue 10–14 yrs•Grey , 15–17 yrs

Genetic Prediction of Obesity Risk

The predictive ability of

the currently

established BMI-

associated loci is poor

2012 Genetic determinants of common obesity and their value in prediction

Influence of Genetics on Human Disease

For any condition the overall balance of

genetic and environmental determinants

can be represented by a point somewhere

within the triangle.

61

Single Locus /

Mendelian

Multiple Loci or multi-chromosomal

Environmental

Cystic Fibrosis

Hemophilia A

Examples:

Alzheimer’s Disease

Type II Diabetes

Cardiovascular Disease

DietCarcinogensInfectionsStressRadiationLifestyle

Gene = F8

Gene= CFTR

F8 = Coagulation Factor VIIICFTR = Cystic Fibrosis Conductance Transmembrane Regulator

Lung Cancer

2008 HMG Genome-based prediction of common diseases- advances and prospects62

2008 HMG Genome-based prediction of common diseases- advances and prospects63

Diabetes ≠ Genetic Disease?

• Familial aggregation – Genetic influences?

– Epigenetic influences• Intrauterine environment

– Shared family environment?• Socioeconomic status

• Dietary preferences

• Food availability

• Gut microbiome content

• Overestimated heritability– Phantom heritability

2012. Drong AW, Lindgren CM, McCarthy MI. Clin Pharmacol Ther. The genetic and epigenetic basis of type 2 diabetes and obesity.2012. PNAS The mystery of missing heritability- Genetic interactions create phantom heritability65

Rare Variant in a Specific Population

• 3756 Latino: whole exome sequencing

A rare functional variant in candidate gene

14276: replication Not found in other ethnic group

2014 JAMA Association of a Low-Frequency Variant in HNF1A With Type 2 Diabetes in a Latino Population

2014 NEJM Null Mutation in Hormone-Sensitive Lipase Gene and Risk of Type 2 Diabetes

Rare Functional Variant = Monogenic Heritable Disease

All Amish

Variants and Disease Susceptibility

2008 NRG Genome-wide association studies for complex traits- consensus, uncertainty and challenges

Genotype Based Diabetes Therapy

Diabetes due to KATP channel mutations sulphonylurea

2007 American Journal of Physiology - Endocrinology and Metabolism. ATP-sensitive K+ channels and disease- from molecule to mala

Mendelian (single-gene) genetic disorderKnown single-gene

candidates testingWhole Genome or Whole

Exome Sequencing

72

Laboratory Director강현석

73

Contents

1. Introduction









7. Medical Images


2012 European Heart Journal. Personalized medicine: hope or hype?

Herceptin

Glivec

76

77

Pharmacogenomic Biomarkers in Drug Labeling (N=166)2015.9.14.Atorvastatin, Azathioprine, Carbamazepine, Carvediolol, Clopidogrel, Codein, Diazepam…..

Large Effect Size Variant?

Disease susceptibility variant Pharmacogenetic variant

EnvironmentalExposure

DrugExposure

Subjects and Strategy

Groups Case 1 Case 2 Control 1 Control 2 Control 3

Role Discovery Discovery Discovery Discovery Validation

StatusAgranulocyto

sis Graves

Agranulocyto

sis Graves

General

Population

General

Population

Graves (no-

agranulocytosis)

Source Hospital Hospital KPGP Open DB Hospital

N 7 19 392 207, 4128 55

Genotyping

WES O O Available

HLA Typing

(6 loci)O Available

Sanger

SequencingO O (n=10) O O

HLA Typing

(3 loci)O (n=8) Available

HLA Typing

(1 locus)O (n=10) O

CHR SNP BP A1 A2Case

Frequency

Control

FrequencyP OR

4 4:36340834 36340834 T C 0.2143 0.002551 4.23E-05 106.6

6 rs112749594 32485397 A G 0.5 0 1.08E-06 NA

6 6:32485410 32485410 T G 0.5 0 1.08E-06 NA

6 6:32485448 32485448 G A 0.5 0 1.08E-06 NA

6 6:32485451 32485451 G A 0.5 0 1.08E-06 NA

6 rs75563047 32485492 T C 0.5 0 1.08E-06 NA

6 rs78287329 32485511 T G 0.5 0 1.08E-06 NA

6 rs115308342 32485705 G A 0.5 0 2.19E-06 NA

6 6:32485722 32485722 A G 0.5 0.006098 9.75E-06 163

6 rs114321399 32487474 A G 0.6 0.005682 2.72E-08 262.5

6 rs77015062 32610825 G A 0.8571 0.2376 2.72E-06 19.25

6 rs9273704 32629297 C T 0.7143 0.1104 4.08E-07 20.15

7 rs3800782 150027763 G A 0.6429 0.1582 7.36E-05 9.581

7 rs76490935 150028098 G A 0.6429 0.1582 7.36E-05 9.581

7 rs11978222 150028400 A G 0.6429 0.1582 7.36E-05 9.581

7 rs3800783 150028542 G A 0.6429 0.1569 6.91E-05 9.673

7 rs114973325 150028664 A G 0.6429 0.1582 7.36E-05 9.581

11 rs7396812 373404 A G 0.7143 0.1724 5.81E-05 12

11 rs7395781 373427 T C 0.7 0.03333 4.74E-05 67.67

11 rs4963161 769188 T C 0.2857 0.01403 7.29E-05 28.11

14 14:23861876 23861876 G T 0.2857 0.005249 4.48E-06 75.8

14 14:64693064 64693064 G T 0.2857 0.006667 8.49E-06 59.6

15 rs75893088 28518102 T C 0.5 0.002551 3.06E-12 391

15 15:28518136 28518136 A G 0.3571 0 7.52E-10 NA

17 17:27071310 27071310 G C 0.2857 0.01306 7.90E-05 30.23

19 rs649216 55324635 C T 0.7143 0.003788 1.68E-14 657.5

23 X:132435892 132435892 T G 0.2143 0.001276 1.71E-05 213.5

Results (1) Variant based approach

GWAS - Manhattan plot

HLA P=2.7 x 10-8

GWS

HERC2P=3.0 x 10-12

KIR2DL4 P=1.7 x 10-14

Results (1) Variant based approach

False Positive

(sequencing technical error)

Genome-Wide Discovery and Validation

Results (2) Gene based approach

Case (N=7)

Sanger

Validation

Control (N=392)

(General

population) Stage 1

8 locus

16 Sample

(case)

Stage 2

2 locus

16 Sample

(case 1 + control 15)

Stage 3

1 locus

40 Sample

(control)

OPN3 : 1HLA-DQB1 : 1

SPA17 : 3TOM1L1 : 2NLRP9 : 1

HLA-DQB1 :1NLRP9 : 1

NLRP9 : 1

Whole Exome Sequencing

Functional Variants

Genetic Prediction

Two Markers CombinedCase Case Case Total Severe Case Control

WES Sanger WES+Sanger WES+Sanger Patient

Total 7 10 17 14 55

High risk genotype 7 8 15 14 19

Low risk genotype 0 2 2 0 36

Variant (%) 100% 80% 88% 100% 35%

OR=14.21, P=1x10-4

Index Agranulocytosis Severe Agranulocytosis

Sensitivity 88% (15/17) 100% (14/14)

Specificity 65% (36/55) 66% (38/58)

Assuming

0.5%

Prevalence

Positive Predictive Value 1.2% 1.5%

Negative Predictive Value 99.9% 100%

Risk (Without testing) 0.5% 0.5%

Results (3) Clinical implication

200 tests needed to avoid 1 case

November 19, 2013

2013 NEJM A Randomized Trial of Genotype-Guided Dosing of Warfarin

2013 NEJM A Randomized Trial of Genotype-Guided Dosing of Warfarin

Median21 days

Median29 days

Median44 days

Median59 days

P<0.001

P=0.003

Expected Metformin response

Other drug Metformin usual dose Metformin low dose (S/E)

0% -1% -2%-1.5% -2.5% -3%+0.5%

HbA1c change

Good ResponseGenotype

Poor ResponseGenotype

Genetics of eating behavior

2011 Genetics of eating behavior

Personalized Medicine

Pharmacogenomics

Nutrigenomics

IRS1 SNP GA/AA

High fat/Low carb

IRS1 SNP GGStandard

Higher effect

Similar effect

2013 Diabetes Care. IRS1 Genotype Modulates Metabolic Syndrome Reversion in Response to 2-Year Weight-Loss Diet Intervention - The POUNDS LOST trial

Gene-Environment Interaction

Gene Environment

Disease

Genetic Predisposition Score Sugar-Sweetened Beverages

Soda School

No-Soda School

Obese Family Lean Family

Genotype Guided Personalized Treatment

Baseline

Genotyping- Drug metabolism- DM etiology- DM complication

1 week 3 month Long term

Genotype based treatment strategy- Drug choice- Drug dose- Lifestyle modification- Complication evaluation

NewT2DM

Pharmacogenetic Tests: 최형진

NoDrug

(N= 10)

Gene

(6 genes=8 bioma

rkers)

Target SNPs

(N=12)

#5

(HJC)Genotype Interpretation Clinical Interpretation

1 Clopidogrel CYP2C19

rs4244285 (G>A) GG*1/*1

(EM)Use standard dosers4986893 (G>A) GG

rs12248560 (C>T) CC

2 Warfarin

VKORC1 rs9923231 (C>T) TTLow dose

(higher risk of bleeding)Warfarin dose=0.5~2 mg/day

CYP2C9rs1799853 (C>T) CC

rs1057910 (A>C) AC

3 Simvastatin SLCO1B1 rs4149056 (T>C) TT Normal

4Azathioprine (AP),

MP, or TGTPMT rs1142345 (A>G) AA Normal

5Carbamazepine

or PhenytoinHLA-B*1502

rs2844682 (C>T) CTNormal

rs3909184 (C>G) CC

6 Abacavir HLA-B*5701 rs2395029 (T>G) TT Normal

7 Allopurinol HLA-B*5801 rs9263726 (G>A) GG Normal

Clopidogrel1): UM/EM=standard dose, IM/PM= consider alternative antiplatelet agent (eg. prasugrel/ticagrelor)

Warfarin2): high dose=5~7 mg/day, medium dose=3~4 mg/day, low dose=0.5~2 mg/day

=0최형진+1,000,000?

Contents

1. Introduction









7. Medical Images


2014 NEJM Genotype–Phenotype Correlation — Promiscuity in the Era of Next-Generation Sequencing

A Genotype-First Approach to Defining

the Subtypes of a Complex Disease

2014.2.27.

Point-of-care GenotypingHyBeacon Probes

Genome Surgery

Future of Genomic Medicine?

Test when neededWithout information Know your type

Bloodtype

Genotype

Here is my

sequence

Contents

1. Introduction









7. Medical Images


111 2015 Sci Transl Med. The emerging field of mobile health

NFC 혈당측정기

114

데이터베이스기반혈당관리

115

혈당변화실시간모니터링

저녁식사전고혈당

117

구글 헬스 앱 분야 매출 1위 ‘눔(noom)’

118

Date Time name foodType calories unit amount2014-08-09 0 미역국 0 23 1국그릇 (300ml) 105 g2014-08-09 0 잡곡밥 0 80 1/4공기 (52.5g) 52 g2014-08-09 0 열무김치 0 3 1/4소접시 (8.75g) 9 g2014-08-09 0 파프리카 0 6 1/2개 (33.25g) 35 g2014-08-09 0 토란대무침 0 28 1/2소접시(46.5g) 46 g2014-08-09 1 복숭아 0 91 1개 (269g) 268 g2014-08-09 2 마른오징어 2 88 1/4마리 (25g) 25 g2014-08-09 2 파프리카 0 6 1/2개 (33.25g) 35 g2014-08-09 2 저지방우유 1 72 1컵 (200ml) 180 g2014-08-09 2 복숭아 0 183 2개 (538g) 538 g2014-08-09 3 복숭아 0 91 1개 (269g) 268 g2014-08-09 3 파프리카 0 6 1/2개 (33.25g) 35 g2014-08-09 4 파프리카 0 6 1/2개 (33.25g) 35 g2014-08-09 4 식빵 1 92 1장 (33g) 33 g2014-08-09 4 삶은옥수수 1 197 1개 반 (150g) 150 g2014-08-09 4 복숭아 0 91 1개 (269g) 268 g2014-08-09 4 저지방우유 1 72 1컵 (200ml) 180 g2014-08-10 0 복숭아 0 91 1개 (269g) 268 g2014-08-10 0 저지방우유 1 36 1/2컵 (100ml) 90 g2014-08-10 0 두부 0 20 1/4인분 (25g) 25 g2014-08-10 0 견과류 2 190 1/4 컵 (50g) 31 g2014-08-10 0 파프리카 0 11 1개 (66.5g) 65 g2014-08-10 2 방울토마토 0 8 4개 (60g) 60 g2014-08-10 2 방울토마토 0 8 4개 (60g) 60 g

121

식사량실시간모니터링

0

100

200

300

400

500

600

아침

아침간식

점심

점심간식

저녁

저녁간식

아침

아침간식

점심

점심간식

저녁

저녁간식

아침

아침간식

점심

점심간식

저녁

저녁간식

아침

아침간식

점심

점심간식

저녁

저녁간식

아침

아침간식

점심

점심간식

저녁

저녁간식

아침

아침간식

점심

점심간식

저녁

저녁간식

아침

아침간식

점심

점심간식

저녁

저녁간식

2014-08-09 2014-08-10 2014-08-11 2014-08-12 2014-08-13 2014-08-14 2014-08-15

점심과식

저녁금식

122

운동량실시간모니터링

0

5000

10000

15000

20000

25000

걸음 수

운동X

123

운동

식사

125

스마트폰활용당뇨병통합관리

의사

상담 교육

조회/분석

교육간호사

매주/필요시

진료 처방

2-3달 간격

평가 회의매주/필요시

식사/운동

스마트폰

데이터베이스 서버

자가관리

전송

분석

혈당측정

혈당측정기

126

피부사진원격진단/처방

129

심전도원격진단/처방

131

133http://startupbank.co.kr/board/board_view.html?ps_boid=75&ps_db=report_s

134 2015 Cell Metabolism. A Smartphone App Reveals Erratic Diurnal Eating Patterns in Humans that Can Be Modulated for Health Benefi

November 3, 2015

135 2015 Cell Metabolism. A Smartphone App Reveals Erratic Diurnal Eating Patterns in Humans that Can Be Modulated for Health Benefi

Personalized Nutrition by

Prediction of Glycemic Responses

136 2015 Cell. Personalized Nutrition by Prediction of Glycemic Responses

Received: October 5, 2015; Received in revised form: October 29, 2015;

Accepted: October 30, 2015;

Contents

1. Introduction









7. Medical Images


Electronic Health Records

2012 NRG Mining electronic health records- towards better research applications and clinical care141

PCA Analysis혈당

신장기능

142

Machine Learning

2014 Big data bioinformatics143

Clinical Notes

144

밤동안저혈당수면 Lt.foot rolling Keep떨림,

식은땀, 현기증, 공복감, 두통, 피로감등의저혈당에 저혈당이있을 즉알려주도록밤사이특이호소수면유지상처와 통증상처부위출혈 oozing, severe pain 알리도록고혈당처방된당뇨식이의중요성과 간식을자제하도록 .고혈당 ,,관리방법 .당뇨약이해잘하고수술부위 oozing Rt.foot rolling

keep드레싱상태를고혈당고혈당 의식변화BST 387 checked.고혈당으로인한구강내감염 위해식후양치, gargle 등구강위생격려.당뇨환자의 발관리방법에 .목표혈당,

목표당화혈색소에 .식사를거르거나지연하지않도록 .식사요법, 운동요법, 약물요법을정확히지키는것이중요을 .처방된당뇨식이의중요성과간식을자제하도록 .고혈당 ,,관리방법 .혈당정상범위임rt foot rolling중으로pain호소밤사이수면양호걱정신경예민감정변화 중임감정을표현하도록지지하고경청기분상태 condition 조금나은듯하다고혈당조절과관련하여 신경쓰는모습보이며혈당 self로측정하는모습보임혈당조절에 안내하고불편감지속알리도록고혈당고혈당 의식변화고혈당 허약감지남력혈당조절안됨고혈당으로 인한구강내감염위해식후양치, gargle 등구강위생격려.당뇨환자의 정기점검내용과빈도에 .BST 140 으로저혈당 호소밤동안저혈당수면 Lt.foot rolling Keep떨림, 식은땀,

현기증, 공복감, 두통, 피로감등의저혈당에저혈당이있을 즉알려주도록 pain 및불편감호소 WA 잘고혈당고혈당 의식변화고혈당허약감지남력혈당조절안됨식사요법,

운동요법, 약물요법을정확히지키는것이중요을 .저혈당/고혈당 과대처법에 .혈당정상화, 표준체중의유지, 정상혈중지질의 유지에 .고혈당 ,,관리방법 .혈당측정법,인슐린자가투여법,

경구투약,수분 섭취량,대체탄수화물,의료진의도움이필요한사항에 교혈당정상범위임수술부위 oozing Rt.foot rolling

keep수술부위 (출혈, 통증, 부종)수술부위

간호기록지 Word Cloud

Natural Language Processing (NLP)145

Contents

1. Introduction









7. Medical Images


Korean Society for Bone and Mineral Research

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

심평원빅데이터연구고혈압약과골절

Choi et al., 2015 International Journal of Cardiology151

Compare Fracture Risk

Comparator?Hypertension

CCBHigh

Blood Pressure

FractureRisk

BB

Non-user

Healthy

Non-user

Cohort study (Health Insurance Review & Assessment Service)New-user design (drug-related toxicity)Non-user comparator (hypertension without medication)

2007 20112008Choi et al., 2015 International Journal of Cardiology152

Contents

1. Introduction









7. Medical Images


2013 Science Structural and Functional Brain Networks- From Connections to Cognition

Green Lines: orexigenic pathwaysRed lines: dopaminergic pathways

2013 The contribution of brain reward circuits to the obesity epidemic2014 Obesity – A neuropsychological disease- Systematic review and neuropsychological mode

A, amygdala; H, hypothalamus; NA, nucleus accumbens, PFC, prefrontal cortex; VTA, ventral tegmental area

156

tDCS Neuromodulation Controls

Feeding Behavior via

Food Reward Activity and Connectivity

Neuromodulation Brain Activity Feeding Behavior

Brain Connectivity

Brain Functional Connectivity

R=0.648p=0.043

tDCS effect onright dlPFC - right thalamusconnectivity

tDCS effect on fullness scoreSpearman’s correlation

dlPFC (dorsolateral prefrontal cortex)

Thalamus

fMRI analysis

2013 Science Functional interactions as big data in the human brain


2012 Decoding subject-driven cognitive states with whole-brain connectivity patterns

2014

Radiomics

2014 Nature Communications. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

Quantitative nuclear morphometry

2015 Laboratory Investigation. Novel genotype-phenotype associations in human cancers enabled by advanced molecular platforms and computational analysis of whole slide images

Contents

1. Introduction









7. Medical Images


Multidimensional Architecture

167

Gene

Hormone

Psychology

Behavior

Phenotype

Outcome

MetabolicDisease

VascularDisease

Environm

ent

Healthcare Big Data

+ Artificial Intelligence

168

Healthcare Big Data Machine Learning

Novel Insights and Applications

173

Medical Eco-system

174

In a scan of 3,000 images, IBM technology was able to spot melanoma with an accuracy of about 95 percent, much better than the 75 percent to 84 percent average of today's largely manual methods.IBM Research will continue to work with Sloan Kettering to develop additional measurements and approaches to further refine diagnosis, as well as refine their approach through larger sets of data.

Dec 17, 2014

175

Aug. 11, 2015

IBM is betting that the same technology that recognizes cats can identify tumors and other signs of diseases. In the long run, IBM and others in the field hope such systems can become reliable advisers to radiologists, dermatologists and other practitioners who analyze images—especially in parts of the world where health-care providers are scarce.While IBM hopes Watson will learn to interpret Merge’s images, it also expects the combination of imagery, medical records and other data to reveal patterns relevant to diagnosis and treatment that a human physician may miss, ushering in an era of computer-assisted care. Two other recent IBM acquisitions, Phytel Inc. and Explorys Inc., yielded 50 million electronic medical records.

177

Environment

Gene

Eat

Exercise

Metabolism

Brain

GlucoseDM

Blood PressureHTN

CardiovascularDisease

Cognitive

Hormone

Behavior

Psychotherapy

Behavior Therapy

Policy Making

Genetic TestingNeuroimaging

Neuromodulation

Drug

Drug

Lab

Survey

Survey

Sensor

DrugDiagnosis

EMR

Government

DataMining

178

Environment Survey

NeuroimagingGenetics Lab/Hormone Hospital

Cognitive

Personalize

Psychotherapy

DietaryIntervention

ExerciseIntervention

Food

Exercise

Glucose

Mobile

Drug

Neuromodulation

Monitoring

CES 2016 후기

삼성전자 C-lab WELT

강 성 지

• 1월 6일~9일

• 17만명 이상 방문

• 프레스 6,000명

• 1조원 이상 매출

그나마 라스베가스라 가능한…

기존 CES 기간

숙소 4만 8000원/박 48만원/박

비행기 왕복 160만원 왕복 290만원

렌트 40만원/주 50만원/주

주차 공간 부족

UBER 가격이 Taxi 보다 비쌈

고든 램지 버거. 1시간 30분 waiting…

메인관

유레카 파크

• 575개 업체 출품

소박한 부스

• 등록비– 1000달러

• 전원+랜선– 1300달러

• 그외,돈만 있으면뭐든지 가능

그래도 사람은 많다

Tip Talk

ZHOR tech

Remo Pill

Withings

Fitbit Blaze

Misfit Ray

Fossil

Sen.se

Sensoria

Under Armour

• http://news.samsung.com/global/video-c-lab-projects-highlight-startup-spirit-inside-samsung

http://news.samsung.com/global/video-c-lab-projects-highlight-startup-spirit-inside-samsung

Smart Interactive Stroke Rehabilitation SystemRAPAEL Smart Glove and system is designed to help people recover from central

nervous system disorders. The games contents of the RAPAEL training system are

designed to delicately induce brain plasticity and guide muscle re-education in stokes

patients.

What is Stroke?Any disease process that disrupts blood flow to a focal region of the brain

- Bleeding into brain and surrounding tissue

- Busted pipe

Ischemic stroke

- Blood clot stops the flow of blood

- Clogged pipe

20%80%Cerebral Hemorrhage

WE INSPIRE HOPE

New view

What is Stroke Rehabilitation?

- Compensation

- The adult brain cannot be changed

Old view

Nudo et al., 1992,

1996

WE INSPIRE HOPE

- Remediation

- We can induce changes in the brain and the

neuromuscular system via exercise and therapy.

→ Neuro-plasticity

What is Stroke Rehabilitation?

Ontario Stroke Rehabilitation Consensus Panel 2007

“Stroke rehabilitation is a progressive,

dynamic, goal-oriented process aimed at

enabling a person with an impairment to

reach his or her optimal physical, cognitive,

emotional, communicative and/or social

functional level.”

WE INSPIRE HOPE

Four Principles for Effective Stroke Rehabilitation

Skill Acquisition of Function Task

- Animal model (Nudo et al., 1996)

- Definite evidences from human studies

(Butefisch, 1995; Wolf et al., 2006; Wolf et al., 2008)

- Limited time of actual therapeutic activity

(Lincoln et al, 1996)

- Reduced quality of life (Duncan et al., 1999)

- Functional task-specific training for stroke patients

(Wolf et al., 2006)

- Goal-oriented functional tasks

(van Vliet et al., 1995; Wu et al., 2000)

Intensive Task Practice

Individualized Adaptive

Training- Practice is “a particular type of repetition”

problem-solving (Bernstein, 1967)

- Voluntary movement > passive movement

(Lotze et al, 2003)

- Active guidance is best for learning

(van Asseldonk et al, 2009)

- Challenging tasks for neurorehabilitation

(Nudo et al., 1996)

- Computational study: Failure in learning too

difficult tasks (Sanger et al, 2004)

- A performance based algorithm

(Choi et al, 2008)

Active Participation

WE INSPIRE HOPE

A more specific method for the principles

Adaptive Practice Scheduler

WE INSPIRE HOPE

More specific rehab tools or robots (for upper extremities)

ADAPT (Choi et al,

2009)

ADLER (Johnson et al,

2006)

AutoCITE (Lum et al, 2005)

WE INSPIRE HOPE

30 minute-session for in and out patients

Big devices occupies space

Only 2 years for medical insurance

Outpatients mostly needs family’s help to visit hospital

Therapists want to be recognized as experts by using

high-tech devices

No robot rehabilitation category for medical insurance

There is not so much ways to show the rehabilitation

progress of patients

Many patients give up rehabilitation

Not so many places to do rehabilitation other than

Hospital

Rehab training is mostly boring to patients

.

.

.

Insights

✓

✓

✓

✓

✓

✓

✓

✓

✓

✓

Reality of Stroke Rehabilitation, Medical ServiceAffinity Analysis (Interview and Observe 5 major rehab hospitals in Korea)

WE INSPIRE HOPE

Persona type

Reality of Stroke Rehabilitation, PatientsBased on analysis of postings in stroke patients’ community

Irrational Rational

Passive

Active

WE INSPIRE HOPE

Emerging Techs in Stroke Rehabilitation

Software for

changing

behaviour(Games and digital

coaching)

Analytics

&

big data

Devices that

Integrate

multiple sensors

and interfaces

Communication

Networks

& tools

WE INSPIRE HOPE

- Emerging Technologies in Physical Therapy and Rehabilitation in Europe, 2013

-

WE INSPIRE YOU TO

HOPE

Rapael smart rehab solution

RAPAEL

Smart Glove

Game-like Exercises Data Visualization

SMARTREHABILITATION

by affordable

device and service

RAPAEL Smart Glove demo video

Values – Physician/Patient/Hospital

WE INSPIRE HOPE

Data-based

Planning &

tracking

MotivationFeeling of

achievement

Reduced resource

requirement

(space, labor, others)

Three principles for product design & development

WE INSPIRE HOPE

Affordabl

e

portabl

e

ligh

t

Hardware – rapael smart Glove Components

WE INSPIRE HOPE

- Tablet PC : Android OS /

Touchscreen

(inc. power adapter &

cord)

- Smart Glove : Left & Right

- Silicone pad : 2 units

- Body band : 2 units

- Battery : 3 units

- Battery charger : 1 unit

- Instruction for user

Smart glove - Key Features & Technologies

WE INSPIRE HOPE

Bending Sensor is a variable resistor that changes

as it is bent. The sensor is connected to computer

system which can accurately compute the amount

of individual finger movements.

Bending sensortechnology

Key

featuresLightweight

Portable

Sensor Technology

Wireless

Ergonomic

Easy wearing

Easy cleansing

✓

✓

✓

✓

✓

✓

✓

- 3 acceleration channels

- 3 angular rate channels

- 3 magnetic field channels

9-axis movement& position sensor

Engineered to be suitable for rehabilitation

process. Luxurious and sophisticated design.

Ultra-low-power energylite32-bit microcontrollers

Software - Rapael rehab platform

WE INSPIRE HOPE

Range of motion (ROM)

- Active

- Passive

Evaluation

- Intensive

- Repetitive

- Task-oriented

(eg. ADL-related)

GAMe-like exercises Performance data

- Play time

- Number of motions

- ROM data

GAMe result

Performance history

- Progress monitoring

- Data sharing via

printing or emailing

Performance report

Rapael rehab platform - evaluation

WE INSPIRE HOPE

PROMNeutral position

aromWith therapist’s help By patient

Rapael rehab platform – Game exercises

WE INSPIRE HOPE

Rapael rehab platform – Performance report

WE INSPIRE HOPE

Performance history by each motion

- Current state, improvement, and progress in the rehabilitation process

Target patients based on field clinical experiences

- Stroke

- SCI (Spinal Cord Injury)

- Parkinson’s disease

- MS (Multiple Sclerosis)

- ALS (Amyotrophic Lateral Sclerosis)

- Rheumatoid arthritis

- Hand burn

- Prosthetic robot hands

WE INSPIRE HOPE

< Stroke

Prosthetic robot hand >

< hand burn

SCI >

Clinical trial results

- Korea National Rehabilitation Center

- Jan – Oct 2014

- Open label designControl (conventional OT) n=14

RAPAEL Smart Glove n=15

- Non-inferiority design

- Statistical superiority proven

- Publication plan (Oct-Nov)

Our roadmap for Smart interactive rehab system

Regulation clearance and plan

WE INSPIRE HOPE

KFDA

FDA

ce C-FDA(complete) (complete)

We won’t let stroke survivors

give up their life

until their full recovery.

Summary

Thank youFor Your Time & Attention!

GET IN TOUCH WITH US

[email protected]