Ms. Jane, Dr. Machine will see you now: Doctorless Healthcare

1. Ms. Jane, Dr.Machine will be here to see
you:
Doctorless Healthcare

2. 40,500
The number of adult patient
deaths in ICU every year
due to misdiagnoses
annually

3. Higher deaths than due to HIV
or Firearms
Injury By
Firearms
33,636
Septicemia
38,156
HIV
6,955
Breast Neoplasm
( Cancer)
41,325
Misdiagnoses*
40,500 Leukemia
23,428
Deaths Reported By CDC
* http://qualitysafety.bmj.com/content/early/2012/07/23/bmjqs-2012-000803.full.pdf+html

4. “A good machine learning
system not only would be
cheaper, more accurate and
objective, but also effectively
replace 80 percent of doctors
simply by being better than the
average doctor.”-
Vinod Khosla

5. 10-15%
DIAGSNOSTIC ERROR
Compare this to prediction
errors from other fields
Electricity Load
Forecasting
+/- 5-8%
Election
Forecast
Nate Silver
=4%
Bookies =
3%
Raymond Kurzweil
14%

6. Is this possible?
Can machine learning really
replace doctors?
What about human to human
interaction, what about
emotions…?
Lets first understand how doctors diagnose ?
Can machines replace doctors?

7. Decision process behind diagnosis
Clinical Question
Run Tests /
Diagnostics
Intervention
Confirmation Bias
Availability Bias
Cognitive Bias

8. Where can the Machine
Learning Help?
Clinical Question
Run Tests /
Diagnostics
Intervention
State
Hypothesis
Run Delphi /
Machine Learning

9. References
• Predicting elections: Who’s the most accurate?
By Timothy Martyn Hill
• 20 percent doctor included: Speculations and musings of a technology optimist
• Googling for a diagnosis—use of Google as a diagnostic aid: internet
based study
• The Art and Science of Clinical Decision Making
• http://profiles.ucsf.edu/gurpreet.dhaliwal
http://qualitysafety.bmj.com/content/early/2012/07/23/bmjqs-2012-000803.full.pdf+html

10. Thank you