This is a keynote talk I gave at the NIPS Conference's Machine Learning for Health workshop in December 2017

1. DEPARTMENT OF
Biomedical Informatics
Artificial Intelligence in
Medicine
That Counts
Isaac ”Zak” Kohane, MD, PhD

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Biomedical Informatics
AI that does what doctors do.
AI that does what doctors don’t do.
AI that does what doctors cannot do.

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Biomedical Informatics
The major contribution of doctors was…

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Biomedical Informatics
ASSAULT
URINARY
INJURY
PSYCH
RESP
GASTRO
E.N.T.
DERM
PAIN
EYE
DENTAL
FEVER/VIRAL
Jane Q. Doe
ED Profile
June,1992 – Feb,1999
INJURY RISK: HIGH
Reis, et al., BMJ 2009

5. DEPARTMENT OF
Biomedical Informatics
A common diagnosis becomes undiagnosed
• 3 years and 10 months old with bloody stool.
• Underwent endoscopy in November 2005 at 4 years old which showed a pancolitis.
• He was started on sulfasalazine; maintained on fish oil and sulfasalazine until age 13 ½ at which
point he flared. That was in July 2015.
• He’s been in a flare since. Unsuccessful wean from prednisone, vancomycin effect transient
• Started on 6MP in March 2016 with no effect over 3 months despite therapeutic levels.
• Started on infliximab 5mg/kg 7/6/2016 with no effect.
• Aug 20th tried a course of Rifaximin with initial, temporally related, transient improvement.
• Has tried multiple forms of PR meds with no effect, including cortisone enemas, cortifoam,
canasa suppos. .
• In September 2016, stool turned bloody and frequency was hourly, hospitalized for tacrolimus
• which improved symptoms but did not produce a remission.
• Vedolizumab was added in October with no appreciable effect.

6. DEPARTMENT OF
Biomedical Informatics
Boundary between diseased and
healthy patients
Can we identify an existing drug that
will move these patients towards the
healthy region?
IBD Expression Profiles:
Whole Blood

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Biomedical Informatics
Tissue: Blood
Drug: Azathioprine

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Biomedical Informatics
Best ranked compound for our patient
• Indirubin
• Chemical compound
most often produced
as a byproduct of
bacterial metabolism
• Constituent of indigo
naturalis (also known
as qing dai),

9. DEPARTMENT OF
Biomedical Informatics
Why not cut out the middleperson?

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Biomedical Informatics
Reverse causality, multiple hypothesis
testing…can and will be addressed

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Biomedical Informatics
Survival 3 Years After a WBC Test
(White, Male, 50-69 Years; Using Last WBC Between 7/28/05 and 7/27/06)

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Biomedical Informatics
When does Medicine succumb to AlphaZero?
• Deterministic.
• Fully observed.
• The action space is discrete.
• Access to a perfect simulator (the
game itself), so the effects of any
action are known exactly.
• Each episode/game is relatively short.
• Evaluation is clear, fast and allows a
lot of trial-and-error experience.
• Huge datasets of human play.
• NOT physiology
• NOT disease course
• NOT drug response
• NOT surgery
• So…. What might succumb…? Which
medical ‘game’ fits the criteria….?
• The game of reimbursement
• Has funded billions of $$ of EHR
• Of ontology wrangling companies etc

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Biomedical Informatics
Bias and fairness: AI applications in medicine
• GAN to maximize
reimbursement
• GAN to
minimize/maximize care
utilization
• Opaque biases in drug or
procedure
recommendations.
•At-will review/exploration
of doctor’s
decisions/advice
•Maximize patient’s utilities
in clinical decision-making
over all achievable
treatment plans
•Netflix for medicine

14. DEPARTMENT OF
Biomedical Informatics
AI -> $$$ <- Platform/Path/Payors
Electronic
Health
Record
Data
(labs, meds, images…)
Summary & Decisions
(Rx, Dx, Prognosis…)
$
Consumers
$Employers
$Government
`

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Biomedical Informatics
Greenfield gone…

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Biomedical Informatics
But at least we have a solid medical education
system…
16
If a test to detect a disease whose
prevalence is 1/1000 has a false positive
rate of 5%, what is the chance that a
person found to have a positive result
actually has the disease, assuming you
know nothing about the person's
symptoms or signs?

17. DEPARTMENT OF
Biomedical Informatics17

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Biomedical Informatics
Young doctors-to-be KNOW that medicine is
an information processing discipline

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Biomedical Informatics
• Who completes the loop?
• Who is trusted?
• Who integrates with rest of care?
• Who oversees
• Process automation?
• Who does expert catch?
• What do you have to show to get
$$$

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Biomedical Informatics

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Biomedical Informatics
Reflections/Conclusion
• How would you like to spend your AI effort chits?
• Doing what doctors are supposed to do at expert level?
• Or by what they cannot do (MD super powers)?
• Most of the interesting part of medicine is not in classification or prediction
• It’s in making the right DECISION for precious human beings faced with suffering/death
• Unless you roll a new one, you have to understand THIS healthcare system
processes NOT just medicine art/science.
• Understanding the “job-to-be-done” and where the $$ coming from as important
as CS/AI +medical expertise.
• Doctors are not necessarily expert in this prioritization.
• Don’t lie, it makes us all look bad.
• YOU can roll a new health care system that is data and knowledge-driven.

22. DEPARTMENT OF
Biomedical Informatics
DATAPOWERED STRATEGIESTO
COUNTERANTIBIOTICRESISTANCE
Harvard Medical School
June 8th 2018
Join us for discussions on ‘omics’, health-services, and
internet data integration for innovation in diagnosis and
treatmentThank you

23. DEPARTMENT OF
Biomedical Informatics
Thank you
Please visit Dbmi.hms.harvard.edu