Providing quality information to doctors in remote areas is essential for better healthcare. Inadequate infrastructure poses a challenge to doctors. As their practice is isolated there is very limited access to quality information. Taking help of their colleagues for second opinion is difficult because of their availability and distance. As life of a patient is in danger, information regarding possible diagnosis becomes crucial. In absence of a solution in existing circumstances, doctor and patient suffer. By leveraging existing internet and mobile technologies one can access high end medical applications. Our mobile app gives diagnostic data and necessary tests for any given patient data. It also has a search engine that retrieves clinical data from web. As the Natural language processing (NLP) is developed using standard medical database (snomed), the search engine yields results better than standard search engine like google. App can be activated by voice, direct text or electronic health record and gives critical diagnostic information to the clinician. The Diagnostic Decision Support System (DDS) is based on methods developed specifically for medical diagnostic domain by experts. By using our DDS one can minimize medical errors and hence treatment costs. The system works over internet and can be accessed remotely through computer or smart phone. The app acts as a colleague for the doctor. It works as a second opinion also. Subsumptive reflection in SNOMED CT: a large description logic-based terminology for diagnosis http://arxiv.org/abs/1512.03516

1. Physician Assistant Artificial Intelligence
Reference System
AM Mohan Rao
Umashankar Adi Kotturu
A. Sri Kailash
www.ai-med.in/pairs/

2. Pain factors
• Misdiagnosis
– Common vs rare disease
• Missed diagnosis
– Errors in clinical data
• Delayed diagnosis
- Complex case
• Treatment costs
- Unnecessary testing
• Drugs
- Side effects
• Reasoning
-Uncertainty of clinical data
• Perception
-Vast domain knowledge
• Diagnostic bias
-Experience
• Inference
-Infection? Neoplasia?
• Training
-Latest advances
Patient Doctor
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3. Solutions
• Internet
- Google search
- Social media
• Colleagues
- Seminars, discussions
• Journals, books
-Access to quality information
• Timely advise
-Emergencies
• Resources
-Limitations in remote settings
• Web application
-Bi-layered Google search
-WhatsApp Messages
• Mobile app
-Artificial intelligence
• Database
-SNOMED CT 426 000 terms
• Diagnostic Decision
Support (DDS)
-Logic & probability
• Natural Language
Processing (NLP)
-Text & XML records
General Ai-med.in
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4. Physician Assistant Artificial Intelligence
Reference System(PAIRS)
• Web application
-Bi-layered Google Search, DDS
• Mobile app
-Android and iPhone, NLP & DDS
• NLP
- Based on SNOMED CT algorithm
• DDS
-Based on Bayesian method
• Database
-PAIRS specific: 18 397 for 485 diseases and 1964 findings
-SNOMED CT: 426 000 terms, 5190055 relationships
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5. Search Engine
PAIRS Google
Bi-layered Single layered
SNOMED CT algorithm + Google search Google search alone
Pathophysiological + Computer based Computer algorithm alone
Context based Word based
Limited relevant search Exhaustive irrelevant search
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6. Google Search
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7. PAIRS Search
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8. PAIRS Google Search
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9. Diagnostic engine
• Inference engine
-3 levels
• Feature given disease
- (a).concomitant in assertion & negation
- (b).concomitant in assertion only
- (c).concomitant in negation only
• Ontological class
-Both system and organ are shared
-Only system is shared
-Neither system nor organ are shared
• Word vectors
-Medical text corpus 50 million words
• Bayesian probability
-Lower bounds
• Feature given disease
-(a). Biopsy (b). Deep tendon
reflexes brisk (c). Loss of
tendon reflexes
• Ontological class
- of disease feature links
• Word vectors
- 485 diseases, 1964 findings
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10. PAIRS DDS
Patient data entry: directly or by file (txt or xml)
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11. PAIRS DDS: Diagnostic types
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12. PAIRS DDS
Diagnostic output for different types
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13. Marketing | strategy
• Licensing
-Hospitals
-Medical colleges
-Residents and Medical students
-Pharmaceutical companies
-Telemedicine
• Advertisement
-Drugs and brands
-Side effects
• Development
-Database
-Diagnosis
• Evaluation
-tertiary hospital
• Publications
-PAIRS evaluations
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14. Team
• AM Mohan Rao
-Full time employee
-Worked in Nobel laureates
environment at a top notch
research institute in US
-Committed to work for
breakthrough technology in
Medicine. 35 years
experience.
• Dr. N.S.N. Rao -Professor of Pediatrics
• Dr. P.N. Rao -Gastroenterologist
• Dr. Ravi Kalaputapu –Strategic advisor
• Uma Shankar Adi
-Entrepreneur and evangelist
-20 years experience
in research and development
• Sri Kailash
Design engineer
• Anand Pothapragada
Web site and MySql
Main Innovator Project associates
Advisors
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15. Financials |Projections
• Product development
completed
• Require evaluations in
hospital for 2-4 months
• Licensing product to
corporate hospitals
• Brands and drug ads to
pharma companies
• Money needed for
office set up
• Build up a team to
include full time
doctors, software and
marketing
professionals.
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16. References
• 1. Subsumptive reflection in SNOMED CT: a large
description logic-based terminology for diagnosis
http://arxiv.org/abs/1512.03516
• 2. Using SNOMED CT concepts for PAIRS
https://www.researchgate.net/publication/221426464_Using_S
NOMED_CT_concepts_for_PAIRS
• 3. And now, artificial intelligence as a medical tool
http://www.thehindu.com/2003/06/09/stories/200306
0903150500.htm
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17. Thank you
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