This is the talk I delivered in one of the seminars organised by ASSOCHAM India in partnership with Department of IT and Electronics, Govt. of WB, India.

1. AI in Healthcare
SUBHENDU DEY (subhendu.dey@in.ibm.com)
Sr. Architect, Global Cognitive Center of Competence, IBM GBS

2. Content
 Introduction to some personas
 Top value-added Healthcare use cases AI can bring in
 Solution Architecture to support such use cases
 Indian context
 Next step for India from the solutions perspective
 Q&A
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3. Meet some of our very known personas 3
Monalisa, a student 2nd grade is suffering from child depression. Her mother uses a healthcare buddy on
her mobile which not only measures the quality time spent with her daughter but also notifies her on social
events where she can take her daughter to. The virtual avatar creates an augmented reality based
environment that has high empathy quotient.
Laltu, a 10 years old boy hails from a village near Kaliaganj, Uttar Dinajpur, is suffering from high fever for
last 3-4 days. There are various kinds of unknown fevers nowadays in the locality, causing huge queue in
nearest health center which is 3 km away. Safiul, Laltu’s father calls a virtual healthcare assistant who speaks
to him in Bengali and advises on therapeutic treatment options based on symptoms.
Dr. Sharma, one of the leading radiologist of the town travels through ~10 diagnostic centers every
weekday to read through brain scan images and write reports. 10 years back he had unbearable workload
causing him not to do full justice to his work always. Now he uses a virtual assistant which can “read”
through the images and can generate report for standard cases.
Dr. Ganguly, one of the leading oncologist nowadays uses a of medical insight advisor which reads through
the medical journals published world wide related to melanoma to distill the information for his effective
consumption. This has been helping him a lot to keep up-to-date on latest R&D, effectiveness of recent
medications on other and accordingly advise treatment.

4. 4
Yes, you guessed it right. These personas exist today but
their activities are futuristic in Indian context! However
that is not fully true in other parts of the world though.
AI is making the personas empowered.

5. Top value-added Healthcare use cases AI can bring in* 5Engagement
Virtual Nursing Assistant • Avatar based augmented reality to respond to
medical symptoms
• Conversation service
• Speech to text and text to speech
• Information retrieval
• Tone analyzer
• Integration through IoT
• Social and other public data
integration
• Cognitive API integration
Healthcare bots • Standard information on medicines
• Appointment and other operations
management
Personal health advisor • Medication alerts and adherence check
• Empathy score and subsequent advise
• Encourage Healthy habits
DataExplorationandInsight
Mining of EMR as well as
other medical records
• Evidence based treatment options
• Targeted treatment (e.g. focus on actionable
genes in case of tumor analysis)
• Precision medicine
• Pharma insights generations
• Medical language understanding
• Hypothesis generation and
inference derivation
• Ranked information retrieval
• Explorative visualizations
• Advanced analytics models
• Deep learning (e.g. CNN)
Improved clinical trials • Easily find potential list of clinical trials for
patient
Drug discovery • Discovery of hidden connections
• Evidence based predictions
Radiology Image analysis • STP for standard cases, human intervention to
critical cases
• Detection of anomalies and alert
* There are other robotics use cases which are not included here.

6. Cognitive elements in Healthcare solutions demands Data,
Analytics + AI focused architecture
 Extract
 Understand
 Relate
 Reason
 Learn
 React
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Application
AI +
Analytics
Data
Cloud
• DATA-DRIVEN ANALYTICS
 Medical Image analytics, patient cohorts, on real world evidence
 Discovery and exploration, statistical modeling, machine learning,
reporting and visualization
• KNOWLEDGE-DRIVEN ANALYTICS
 Annotator on clinical data, medical insight, patient insight
 NLU and classifier, Cognitive pipeline, Knowledge base and query,
concept detection
• Infrastructure
• Dependability
• Security / Compliance
• DevOps
• Data pipeline – ingest/transform/persist in data lake
• Core Health Services – FHIR, Master patient index, medication DB etc.
• Data Governance – consent, de-identification, audit etc.
• Healthcare solution for end-users
• Developer experience including the based services / boiler-plates
• Client and application services

7. Indian context – there is a clear demand*
 69.2 million Indians suffer from Diabetes as per data from World Health
Organization. Prevalence of diabetic retinopathy (DR) in patients with
diabetes was recently estimated to be 34.6%.
 For every 1681 citizens in India, there is only one doctor available as per
medical council of India report published in May 2016.
 68.84% of population reside in rural India as per recent census. Last mile
delivery of healthcare amenities is still a major challenge in India, especially to
places that lack the connectivity of routes.
 India is known to suffer from a dual disease burden. While the country has
witnessed and cured chronic diseases, it still hasn’t overcome challenges
posed by infectious diseases and malnutrition. Decentralization of diagnostic
testing needs to be inculcated through AI based diagnostic technology.
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* Sourced from ET Healthworld, December 26 2016

8. Next steps for India – from solutions perspective
 A large part of healthcare specific NLP services are English based.
 Any AI based solution depends on large amount of data. India at a country level needs
to come up with clear policy on citizens health record.
 Even a large amount of urban health record is not effectively digitized yet.
 A common information standard like FHIR should be adhered to.
 As evident from the architecture, cloud based solution is almost inevitable. A clear
governance policy needs to be established on data security and privacy.
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9. Q&A 9

10. References
 Frost & Sullivan analysis: From $600 M to $6 Billion, Artificial Intelligence Systems Poised for
Dramatic Market Expansion in Healthcare.
 Accenture report: Artificial Intelligence: Healthcare’s new Nervous System
 IBM Watson health offering
 Sense.ly – the virtual nurse
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