2. Autonomous Medicine: Computer-Assisted Diagnosis Cancer Detection
Sharmila Anandasabapathy, MD
Professor of Medicine in Gastroenterology
Director, Baylor Global Health
Baylor College of Medicine

3. Challenges in Endoscopic Cancer Screening in Remote Settings Globally
Clinicians: less experienced
Environment:
infrastructure
power
geography: loss of follow up, no “back up”
Cost
Technical support: limited

4. Portable Microendoscopy: Experiences in China, Honduras, Africa

5. Image Analysis Software
Blue outline – ROI
Red outline – enlarged/abnormal nuclei
056_27_007
Yellow outline – nuclei

6. Normal
02_01_006-normal

7. Normal (with software) overlay
% abnormal nuclei: 13.5

8. Early Cancer
164_80_001-high grade

9. Early Cancer (Software Overlay)
% abnormal nuclei: 30.9

10. Summary
No significant difference in pre- and post-software read among experts
Significant increase in accuracy among novices
Specificity went up significantly
This leads to greatest improvement in “yield” & impact
“False positives” are an issue with standard screening
Increased confidence among all providers = more likely to act on diagnosis (treat, biopsy, NOT biopsy, etc.)

11. What does this Mean for Software-Assist
Clinician Confidence & Impact
A software-assisted diagnosis increases confidence uniformly
Confidence translates to point-of-care decisions
Experience of Provider is Key: Who is user?
Novices rely on software
Experienced providers rely on themselves
Implications for Space and Remote Settings?
Skill level is critical:
Novices will rely on software (often regardless of accuracy of software)
Human Factors element:
Effect of stress on confidence and decisions