Exponential growth in data to analyze using AI in many fields In healthcare: – Medical Imaging – Electronic health records – Genomic data – Patient
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Dr. Keith Dreyer
Chief Data Science Officer, MGH, BWH, Partners Healthcare Associate Professor of Radiology, Harvard Medical School Chief Science Officer, American College of Radiology Data Science Institute ACR Board of Chancellors, Chairman Informatics CommissionHealthcare AI
2Help sick patients get healthy as soon as possible
Our Role as Physicians
21Prevent illness
3Stabilize & manage patients with chronic conditions
Healthcare Spending as a Percentage of GDP (1995-2014) 19992015
Institute of Medicine: Improving Diagnosis In Health Care
Radiologist Relevance In Error Reduction
6Improving the health
of populationsImproving the individual
experience of careReducing the per capita
costs of careImproving the work life of those who deliver care Data Science and Artificial Intelligence: A Rapidly Emerging Megatrend in Business and Society Hype? Yes.Reality?
Yes. Convergence of rapid advances and growth on multiple fronts:1.Storage and processing power as a cheap, on-demand utility:
Graphics Processing Units (GPUs)
Cloud computing allows affordable GPUs at scale
2.Exponential growth in data to analyze using AI in many fields.
In healthcare:
Medical Imaging
Electronic health records
Genomic data
Patient monitoring and treatment devices (e.g., EKG, Pulse,Oxygen, IV Pumps, etc..)
Consumer biomonitoring devices (e.g., Fitbit, Apple Watch, smartphones)High resolution imaging devices
Data registries
Environmental data
Evidence-based guidelines
Clinical trial and other research data
Medical literature and supporting primary data
growth in AI applications in the last 5 years? These technological advances and data growth have spurred:1.Powerful new applications for known AI techniques
(e.g., deep learning)2.A global, online community of AI practitioners sharing
advances daily3.Open source software from the community and tech
4.HugeAI investments from tech titans who see AI as a
strategic asset growth in AI applications in the last 5 years? Data Science is an interdisciplinary field that allows its practitioners to understand and analyze actual phenomena with data. complementary but distinct areas:1.Mathematics and Statistics
2.Computer science & the sub-fields of artificial intelligence and
machine learning3.Subject matter knowledge about the analysis topic (i.e., How that
Definition of Data Science
AI HEALTHCARE
PUBLICATION
ACTIVITY
Deep Learning for Health Informatics -Daniele Ravi, et. al., IEEE Journal of Biomedical and Health Informatics, Vol. 21, No. 1,January 2017
Financial Power: Corporate Valuations by Sector
0 100200
300
400
500
600
700
800
SpeechEHRInsuranceDiagnosticsAI Tech Giants
AMAZON
MICROSOFT
PHILIPS
SIEMENS
GEEPICCERNERNUANCE
MARKET
CAP (BILLIONS AETNAANTHEM
UNITED
($3 TRILLION)NVIDIA
Financial Power: Corporate Valuations by Sector
($3 TRILLION) 0 100200
300
400
500
600
700
800
SpeechEHRInsuranceDiagnosticsAI Tech Giants
AMAZON
MICROSOFT
PHILIPS
SIEMENS
GEEPICCERNERNUANCE
MARKET
CAP (BILLIONS AETNAANTHEM
UNITED
NVIDIA
Data Science, Artificial Intelligence and Healthcare $3.3 TrillionUS HEALTHCARE COSTS
($3.3 TRILLION)Medical Imaging Expenses
330 Million Individuals
x $10,000 per Person $3 TrillionImaging ($300 Billion)
US HEALTHCARE COSTS
($3.3 TRILLION)Medical Imaging Expenses
10% $3 TrillionImaging Acquisition
($270 Billion)Imaging Interpretation
($30 Billion)US HEALTHCARE COSTS
($3.3 TRILLION)Medical Imaging Expenses
<1%Making imaging safe, effective and accessible
to those who need it. 36Kmembers75+ years
Core Purpose
To serve patients and society by empowering members to advance the practice, science, and professions of radiological care. 20K digital facilitiesThe ACR: Leading the Way
230 2000
4000
6000
8000
10000
12000
2012
Q4 2013
Q1 2013
Q2 2013
Q3 2013
Q4 2014
Q1 2014
Q2 2014
Q3 2014
Q4 2015
Q1 2015
Q2 2015
Q3 2015
Q4 2016
Q1 2016
Q2 2016
Q3
Registries
Accreditation
Clinical Trials
T RANSFER
OF I MAGES A ND D ATAImaging Facilities Digitally Connected to ACR
>12,000Radiologist Relevance In Error Reduction
3 Key Actions:
Imaging 3.0 is a vision and strategy for
providing optimal imaging care.Imaging 3.0: Value-Based Radiology
28Culture
Change
Portfolio
of IT ToolsAlignment of
Incentives
AI AI IN CLINICAL
DIAGNOSTICS
CLASSIFY
DETECT
AI IN DIAGNOSTICS
DECISION
EXAMCLASSIFY
REPORT
VISUALIZE
RESULT
DETECT
Imaging 3.0 is a vision and game plan
for providing optimal imaging care.Imaging 3.0: Value-Based Radiology
32Clinical Decision Support for Image Ordering
Providing for millions of examinations per year
3 Key Actions:
Culture
Change
Portfolio
of IT ToolsAlignment of
Incentives
AI IN DIAGNOSTICS
DECISION
EXAMCLASSIFY
REPORT
VISUALIZE
RESULT
DETECT
T HE ACR APPROPRIATENESS
CRITERIA
149 AUC Topics
705 AUC Scenarios
6,184 AUC Rules
5,907 Literature References
20 years of continuous work
Hundreds of clinical experts
Multi-specialty based
Rigorous SOE methodology
AHRQ NGC transparency
Continuous updates
Widely referenced
(416) Multidisciplinary JournalsRadiology
1,960Over 30
Specialties
3,947ACR AUC
Comprehensive Multidisciplinary Evidence Base
References = 5,907 Articles (416 Journals)
41 (8)Endocrinology
35 (8)Rheumatology
26 (1)Nephrology
21 (1)Genomics
17 (2)Family Medicine
13 (1)Psychiatry
10 (3)Sports Medicine
9 (3)Infectious Disease
9 (4)Pathology
7 (2)Epidemiology
6 (1)Medical Physics
5 (1)Immunology
3 (1)Dermatology
2 (1)Geriatrics
2 (1)Ophthalmology
489 (42)Oncology
447 (38)Surgery
445 (33)Medicine
346 (21)Urology
305 (29)Cardiology
263 (37)Neurology
261 (21)Gynecology
258 (3)Radiation Oncology
181 (28)Gastroenterology
152 (16)Pediatrics
150 (8)Emergency Medicine
121 (6)Nuclear Medicine
115 (13)Orthopedics
110 (11)Pulmonology
50 (13)Vascular
48 (12)ENT
33%67%
5,907 Multidisciplinary Articles
Radiology
(47)Over 30
Specialties
(369)11%89%
5,907 Articles
416 Journals
36EHR I