SlideShare a Scribd company logo
1 of 15
Download to read offline
AI for COVID-19: An online virtual care
approach
X. Amatriain, PhD Geoff Tso, MD Anitha Kannan, PhD
COVID-19 and AI Virtual Conference
Stanford 04/01/2020
AI-powered virtual care
for everyone
● >50% world with no access to
essential health services
○ ~30% of US adults under-insured
● ~15 min. to capture information,
diagnose, recommend treatment
● ⅓ of Americans self-diagnose
online
Healthcare access and scalability
shortage of 120,000 physicians by 2030
Towards AI powered scalable health systems
● Mobile-First Care, always
on, accessible, affordable
● AI + human providers in
the loop for quality care
● Always-Learning system
● AI to operate in-the-wild
(EHR)
How does this look like?
Our approach to COVID-19
Personalized Diagnostic Assessment
AI + Providers in the loop + Daily follow up
Working on...
● Added at-home testing
capabilities to our platform,
waiting for FDA to approve
● In discussions with existing
health systems who may
use platform to scale and
improve access
Peer-reviewed research at Curai
Question similarity
● Transfer learning
● Double-finetune BERT model
● Handle data sparsity
● Medical domain knowledge
through an intermediate QA binary
task
● Out-of-the-box applied to
COVID specific Q/A
BERT
pre-trained
weights
BERT
question
Label Loss
answer
BERT
Q
Label Loss
Q
QA
Automated Question/Answering
User Questions
Matching Questions in our FAQ
(Answer not shown here for brevity)
When do COVID symptoms start after exposure? How long is it between when a person is exposed to the
virus and when they start showing symptoms?
I am asymptomatic and have been social
distancing/self-isolating for the past x days. Can I
still transmit the infection?
How can someone pass along coronavirus when
asymptomatic? If not sneezing or coughing, how can they
infect others?
Currently I’m experiencing a cough and slight
chest pain. Should I just stay at home? At what
point will I know I have to go to the ER?
When should you go to
the emergency room?
● Automated question answering via question similarity
● Practitioners’ vetted answers with ability to follow up
ML + Expert systems for Dx models
female
middle aged
fever
cough
Influenza 16.9
bacterial pneumonia 16.9
acute sinusitis 10.9
asthma 10.9
common cold 10.9
influenza 0.753
bacterial pneumonia 0.205
asthma 0.017
acute sinusitis 0.008
pulmonary tuberculosis 0.007
Inputs
DDx with expert systems DDx with ML model
Expert
system
Clinical case
simulator
Clinical cases
DDx
ML
model
Common cold
UTI
Acute bronchitis
Female
Middle-aged
Chronic cough
Nasal congestion
Other data
(e.g. EHR)
Feedback loop
Inputs DDx before COVID DDx after COVID
female
middle aged
fever
cough
healthcare worker
influenza 0.753
bacterial pneumonia 0.205
asthma 0.017
acute sinusitis 0.008
pulmonary tuberculosis 0.007
COVID-19 0.913
influenza 0.048
bacterial pneumonia 0.024
pulmonary tuberculosis 0.004
adenovirus infection 0.003
female
middle aged
fever
cough
nasal congestion
influenza 0.634
adenovirus infection 0.159
bacterial pneumonia 0.114
acute sinusitis 0.05
asthma 0.019
influenza 0.512
COVID-19 0.256
adenovirus infection 0.106
bacterial pneumonia 0.069
acute sinusitis 0.026
Conclusions
● Healthcare needs to scale quickly, and this has become obvious in a global
pandemic like the one we are facing
● The only way to scale healthcare while improving quality and accessibility is
through technology and AI
● AI cannot be simply “dropped” in the middle of old workflows and approaches
○ It needs to be integrated in end-to-end medical care benefitting both patients and providers

More Related Content

What's hot

How Real-time Analysis turns Big Medical Data into Precision Medicine
How Real-time Analysis turns Big Medical Data into Precision MedicineHow Real-time Analysis turns Big Medical Data into Precision Medicine
How Real-time Analysis turns Big Medical Data into Precision MedicineMatthieu Schapranow
 
Introduction to Healthcare Analytics
Introduction to Healthcare Analytics Introduction to Healthcare Analytics
Introduction to Healthcare Analytics Experfy
 
GuoJian CV2014.6.26提交
GuoJian CV2014.6.26提交GuoJian CV2014.6.26提交
GuoJian CV2014.6.26提交JIan Guo
 
Healthcare analytics
Healthcare analytics Healthcare analytics
Healthcare analytics Arun K
 
Statistics For Health Science and Its Impacts
Statistics For Health Science and Its ImpactsStatistics For Health Science and Its Impacts
Statistics For Health Science and Its ImpactsCashews
 
Analytics in healthcare
Analytics in healthcareAnalytics in healthcare
Analytics in healthcareAnushkaAlok
 
Health Informatics- UMKC, Presentation
Health Informatics- UMKC, Presentation Health Informatics- UMKC, Presentation
Health Informatics- UMKC, Presentation Nikhil Kassetty
 
IRJET - An Effective Stroke Prediction System using Predictive Models
IRJET -  	  An Effective Stroke Prediction System using Predictive ModelsIRJET -  	  An Effective Stroke Prediction System using Predictive Models
IRJET - An Effective Stroke Prediction System using Predictive ModelsIRJET Journal
 
Data explosion in medicine: challenges and opportunities
Data explosion in medicine: challenges and opportunitiesData explosion in medicine: challenges and opportunities
Data explosion in medicine: challenges and opportunitiesOurlad Alzeus Tantengco
 
BYO App: Announcing Linq from Open mHealth
BYO App: Announcing Linq from Open mHealthBYO App: Announcing Linq from Open mHealth
BYO App: Announcing Linq from Open mHealthIda Sim
 
Predictive Analytics in Healthcare
Predictive Analytics in HealthcarePredictive Analytics in Healthcare
Predictive Analytics in HealthcareICFAIEDGE
 
Application of business analytics in healthcare
Application of business analytics in healthcareApplication of business analytics in healthcare
Application of business analytics in healthcareAnnElizabeth8
 

What's hot (20)

How Real-time Analysis turns Big Medical Data into Precision Medicine
How Real-time Analysis turns Big Medical Data into Precision MedicineHow Real-time Analysis turns Big Medical Data into Precision Medicine
How Real-time Analysis turns Big Medical Data into Precision Medicine
 
Overview of Health IT
Overview of Health ITOverview of Health IT
Overview of Health IT
 
Introduction to Healthcare Analytics
Introduction to Healthcare Analytics Introduction to Healthcare Analytics
Introduction to Healthcare Analytics
 
GuoJian CV2014.6.26提交
GuoJian CV2014.6.26提交GuoJian CV2014.6.26提交
GuoJian CV2014.6.26提交
 
Venkatesh_CV
Venkatesh_CVVenkatesh_CV
Venkatesh_CV
 
Healthcare analytics
Healthcare analytics Healthcare analytics
Healthcare analytics
 
Statistics For Health Science and Its Impacts
Statistics For Health Science and Its ImpactsStatistics For Health Science and Its Impacts
Statistics For Health Science and Its Impacts
 
Analytics in healthcare
Analytics in healthcareAnalytics in healthcare
Analytics in healthcare
 
Data to help patients 101
Data to help patients 101Data to help patients 101
Data to help patients 101
 
Computer science for health
Computer science for healthComputer science for health
Computer science for health
 
Health Informatics- UMKC, Presentation
Health Informatics- UMKC, Presentation Health Informatics- UMKC, Presentation
Health Informatics- UMKC, Presentation
 
IRJET - An Effective Stroke Prediction System using Predictive Models
IRJET -  	  An Effective Stroke Prediction System using Predictive ModelsIRJET -  	  An Effective Stroke Prediction System using Predictive Models
IRJET - An Effective Stroke Prediction System using Predictive Models
 
resume
resumeresume
resume
 
Stroke Prediction
Stroke PredictionStroke Prediction
Stroke Prediction
 
Data explosion in medicine: challenges and opportunities
Data explosion in medicine: challenges and opportunitiesData explosion in medicine: challenges and opportunities
Data explosion in medicine: challenges and opportunities
 
BYO App: Announcing Linq from Open mHealth
BYO App: Announcing Linq from Open mHealthBYO App: Announcing Linq from Open mHealth
BYO App: Announcing Linq from Open mHealth
 
Predictive Analytics in Healthcare
Predictive Analytics in HealthcarePredictive Analytics in Healthcare
Predictive Analytics in Healthcare
 
Resume dec2015
Resume dec2015Resume dec2015
Resume dec2015
 
Careum
CareumCareum
Careum
 
Application of business analytics in healthcare
Application of business analytics in healthcareApplication of business analytics in healthcare
Application of business analytics in healthcare
 

Similar to AI for COVID-19: An online virtual care approach

Digitalization in obgyn
Digitalization in obgynDigitalization in obgyn
Digitalization in obgynManik Gurram
 
20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenleving20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenlevingAnn Huygelier
 
20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenleving20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenlevingD3 Consutling
 
Data/AI driven product development: from video streaming to telehealth
Data/AI driven product development: from video streaming to telehealthData/AI driven product development: from video streaming to telehealth
Data/AI driven product development: from video streaming to telehealthXavier Amatriain
 
Personal health records presentation at Cambridge Refresh
Personal health records presentation at Cambridge RefreshPersonal health records presentation at Cambridge Refresh
Personal health records presentation at Cambridge RefreshMohammad Al-Ubaydli
 
Digital transformation and application of iot to healthcare
Digital transformation and application of iot to healthcareDigital transformation and application of iot to healthcare
Digital transformation and application of iot to healthcaresandhibhide
 
How to Protect Patient Data in an Increasingly Social Healthcare Industry
How to Protect Patient Data in an Increasingly Social Healthcare IndustryHow to Protect Patient Data in an Increasingly Social Healthcare Industry
How to Protect Patient Data in an Increasingly Social Healthcare IndustryPerficient, Inc.
 
apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...
apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...
apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...apidays
 
Microsoft for healthcare storytelling
Microsoft for healthcare    storytellingMicrosoft for healthcare    storytelling
Microsoft for healthcare storytellingAdrien Lainé ✪
 
The Digital Age: How Clinical Software Tools are transforming the patient exp...
The Digital Age: How Clinical Software Tools are transforming the patient exp...The Digital Age: How Clinical Software Tools are transforming the patient exp...
The Digital Age: How Clinical Software Tools are transforming the patient exp...Train IT Medical
 
Qrepublik MedID Presentation Product (NEW)_compressed.pdf
Qrepublik MedID Presentation Product (NEW)_compressed.pdfQrepublik MedID Presentation Product (NEW)_compressed.pdf
Qrepublik MedID Presentation Product (NEW)_compressed.pdfQREPUBLIC, INC.
 
Health Information Exchange
Health Information ExchangeHealth Information Exchange
Health Information ExchangeKatie Parker
 
Diabetes therapies and technology: implications for doctors and patients
Diabetes therapies and technology: implications for doctors and patientsDiabetes therapies and technology: implications for doctors and patients
Diabetes therapies and technology: implications for doctors and patientsHealthXn
 
Telehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and DiagnosticsTelehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and DiagnosticsAmmar
 
Preparing for the Future Innovation in Digital Healthcare: Manas Tripathi
Preparing for the Future Innovation in Digital Healthcare: Manas TripathiPreparing for the Future Innovation in Digital Healthcare: Manas Tripathi
Preparing for the Future Innovation in Digital Healthcare: Manas TripathiRahul Neel Mani
 

Similar to AI for COVID-19: An online virtual care approach (20)

Digitalization in obgyn
Digitalization in obgynDigitalization in obgyn
Digitalization in obgyn
 
20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenleving20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenleving
 
20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenleving20130226 impact van zorg 2 0 op onze samenleving
20130226 impact van zorg 2 0 op onze samenleving
 
Prairie dev con june 2015
Prairie dev con   june 2015Prairie dev con   june 2015
Prairie dev con june 2015
 
Capita Selecta
Capita SelectaCapita Selecta
Capita Selecta
 
Data/AI driven product development: from video streaming to telehealth
Data/AI driven product development: from video streaming to telehealthData/AI driven product development: from video streaming to telehealth
Data/AI driven product development: from video streaming to telehealth
 
Personal health records presentation at Cambridge Refresh
Personal health records presentation at Cambridge RefreshPersonal health records presentation at Cambridge Refresh
Personal health records presentation at Cambridge Refresh
 
Digital transformation and application of iot to healthcare
Digital transformation and application of iot to healthcareDigital transformation and application of iot to healthcare
Digital transformation and application of iot to healthcare
 
How to Protect Patient Data in an Increasingly Social Healthcare Industry
How to Protect Patient Data in an Increasingly Social Healthcare IndustryHow to Protect Patient Data in an Increasingly Social Healthcare Industry
How to Protect Patient Data in an Increasingly Social Healthcare Industry
 
Jwt i health trends report
Jwt i health trends reportJwt i health trends report
Jwt i health trends report
 
apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...
apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...
apidays LIVE India - The digitisation of healthcare by Dr S.S. Lal, Global Fo...
 
Microsoft for healthcare storytelling
Microsoft for healthcare    storytellingMicrosoft for healthcare    storytelling
Microsoft for healthcare storytelling
 
Digital Health in times of COVID
Digital Health in times of COVIDDigital Health in times of COVID
Digital Health in times of COVID
 
The Digital Age: How Clinical Software Tools are transforming the patient exp...
The Digital Age: How Clinical Software Tools are transforming the patient exp...The Digital Age: How Clinical Software Tools are transforming the patient exp...
The Digital Age: How Clinical Software Tools are transforming the patient exp...
 
China tencent MJ
China tencent MJChina tencent MJ
China tencent MJ
 
Qrepublik MedID Presentation Product (NEW)_compressed.pdf
Qrepublik MedID Presentation Product (NEW)_compressed.pdfQrepublik MedID Presentation Product (NEW)_compressed.pdf
Qrepublik MedID Presentation Product (NEW)_compressed.pdf
 
Health Information Exchange
Health Information ExchangeHealth Information Exchange
Health Information Exchange
 
Diabetes therapies and technology: implications for doctors and patients
Diabetes therapies and technology: implications for doctors and patientsDiabetes therapies and technology: implications for doctors and patients
Diabetes therapies and technology: implications for doctors and patients
 
Telehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and DiagnosticsTelehealth Remote Monitoring and Diagnostics
Telehealth Remote Monitoring and Diagnostics
 
Preparing for the Future Innovation in Digital Healthcare: Manas Tripathi
Preparing for the Future Innovation in Digital Healthcare: Manas TripathiPreparing for the Future Innovation in Digital Healthcare: Manas Tripathi
Preparing for the Future Innovation in Digital Healthcare: Manas Tripathi
 

More from Xavier Amatriain

AI-driven product innovation: from Recommender Systems to COVID-19
AI-driven product innovation: from Recommender Systems to COVID-19AI-driven product innovation: from Recommender Systems to COVID-19
AI-driven product innovation: from Recommender Systems to COVID-19Xavier Amatriain
 
Lessons learned from building practical deep learning systems
Lessons learned from building practical deep learning systemsLessons learned from building practical deep learning systems
Lessons learned from building practical deep learning systemsXavier Amatriain
 
From one to zero: Going smaller as a growth strategy
From one to zero: Going smaller as a growth strategyFrom one to zero: Going smaller as a growth strategy
From one to zero: Going smaller as a growth strategyXavier Amatriain
 
Recommender Systems In Industry
Recommender Systems In IndustryRecommender Systems In Industry
Recommender Systems In IndustryXavier Amatriain
 
Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...
Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...
Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...Xavier Amatriain
 
Past present and future of Recommender Systems: an Industry Perspective
Past present and future of Recommender Systems: an Industry PerspectivePast present and future of Recommender Systems: an Industry Perspective
Past present and future of Recommender Systems: an Industry PerspectiveXavier Amatriain
 
Staying Shallow & Lean in a Deep Learning World
Staying Shallow & Lean in a Deep Learning WorldStaying Shallow & Lean in a Deep Learning World
Staying Shallow & Lean in a Deep Learning WorldXavier Amatriain
 
Machine Learning for Q&A Sites: The Quora Example
Machine Learning for Q&A Sites: The Quora ExampleMachine Learning for Q&A Sites: The Quora Example
Machine Learning for Q&A Sites: The Quora ExampleXavier Amatriain
 
BIG2016- Lessons Learned from building real-life user-focused Big Data systems
BIG2016- Lessons Learned from building real-life user-focused Big Data systemsBIG2016- Lessons Learned from building real-life user-focused Big Data systems
BIG2016- Lessons Learned from building real-life user-focused Big Data systemsXavier Amatriain
 
Strata 2016 - Lessons Learned from building real-life Machine Learning Systems
Strata 2016 -  Lessons Learned from building real-life Machine Learning SystemsStrata 2016 -  Lessons Learned from building real-life Machine Learning Systems
Strata 2016 - Lessons Learned from building real-life Machine Learning SystemsXavier Amatriain
 
Past, present, and future of Recommender Systems: an industry perspective
Past, present, and future of Recommender Systems: an industry perspectivePast, present, and future of Recommender Systems: an industry perspective
Past, present, and future of Recommender Systems: an industry perspectiveXavier Amatriain
 
Barcelona ML Meetup - Lessons Learned
Barcelona ML Meetup - Lessons LearnedBarcelona ML Meetup - Lessons Learned
Barcelona ML Meetup - Lessons LearnedXavier Amatriain
 
10 more lessons learned from building Machine Learning systems - MLConf
10 more lessons learned from building Machine Learning systems - MLConf10 more lessons learned from building Machine Learning systems - MLConf
10 more lessons learned from building Machine Learning systems - MLConfXavier Amatriain
 
10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systemsXavier Amatriain
 
Machine Learning to Grow the World's Knowledge
Machine Learning to Grow  the World's KnowledgeMachine Learning to Grow  the World's Knowledge
Machine Learning to Grow the World's KnowledgeXavier Amatriain
 
MLConf Seattle 2015 - ML@Quora
MLConf Seattle 2015 - ML@QuoraMLConf Seattle 2015 - ML@Quora
MLConf Seattle 2015 - ML@QuoraXavier Amatriain
 
Lean DevOps - Lessons Learned from Innovation-driven Companies
Lean DevOps - Lessons Learned from Innovation-driven CompaniesLean DevOps - Lessons Learned from Innovation-driven Companies
Lean DevOps - Lessons Learned from Innovation-driven CompaniesXavier Amatriain
 
10 Lessons Learned from Building Machine Learning Systems
10 Lessons Learned from Building Machine Learning Systems10 Lessons Learned from Building Machine Learning Systems
10 Lessons Learned from Building Machine Learning SystemsXavier Amatriain
 
Recsys 2014 Tutorial - The Recommender Problem Revisited
Recsys 2014 Tutorial - The Recommender Problem RevisitedRecsys 2014 Tutorial - The Recommender Problem Revisited
Recsys 2014 Tutorial - The Recommender Problem RevisitedXavier Amatriain
 
Kdd 2014 Tutorial - the recommender problem revisited
Kdd 2014 Tutorial -  the recommender problem revisitedKdd 2014 Tutorial -  the recommender problem revisited
Kdd 2014 Tutorial - the recommender problem revisitedXavier Amatriain
 

More from Xavier Amatriain (20)

AI-driven product innovation: from Recommender Systems to COVID-19
AI-driven product innovation: from Recommender Systems to COVID-19AI-driven product innovation: from Recommender Systems to COVID-19
AI-driven product innovation: from Recommender Systems to COVID-19
 
Lessons learned from building practical deep learning systems
Lessons learned from building practical deep learning systemsLessons learned from building practical deep learning systems
Lessons learned from building practical deep learning systems
 
From one to zero: Going smaller as a growth strategy
From one to zero: Going smaller as a growth strategyFrom one to zero: Going smaller as a growth strategy
From one to zero: Going smaller as a growth strategy
 
Recommender Systems In Industry
Recommender Systems In IndustryRecommender Systems In Industry
Recommender Systems In Industry
 
Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...
Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...
Recsys 2016 tutorial: Lessons learned from building real-life recommender sys...
 
Past present and future of Recommender Systems: an Industry Perspective
Past present and future of Recommender Systems: an Industry PerspectivePast present and future of Recommender Systems: an Industry Perspective
Past present and future of Recommender Systems: an Industry Perspective
 
Staying Shallow & Lean in a Deep Learning World
Staying Shallow & Lean in a Deep Learning WorldStaying Shallow & Lean in a Deep Learning World
Staying Shallow & Lean in a Deep Learning World
 
Machine Learning for Q&A Sites: The Quora Example
Machine Learning for Q&A Sites: The Quora ExampleMachine Learning for Q&A Sites: The Quora Example
Machine Learning for Q&A Sites: The Quora Example
 
BIG2016- Lessons Learned from building real-life user-focused Big Data systems
BIG2016- Lessons Learned from building real-life user-focused Big Data systemsBIG2016- Lessons Learned from building real-life user-focused Big Data systems
BIG2016- Lessons Learned from building real-life user-focused Big Data systems
 
Strata 2016 - Lessons Learned from building real-life Machine Learning Systems
Strata 2016 -  Lessons Learned from building real-life Machine Learning SystemsStrata 2016 -  Lessons Learned from building real-life Machine Learning Systems
Strata 2016 - Lessons Learned from building real-life Machine Learning Systems
 
Past, present, and future of Recommender Systems: an industry perspective
Past, present, and future of Recommender Systems: an industry perspectivePast, present, and future of Recommender Systems: an industry perspective
Past, present, and future of Recommender Systems: an industry perspective
 
Barcelona ML Meetup - Lessons Learned
Barcelona ML Meetup - Lessons LearnedBarcelona ML Meetup - Lessons Learned
Barcelona ML Meetup - Lessons Learned
 
10 more lessons learned from building Machine Learning systems - MLConf
10 more lessons learned from building Machine Learning systems - MLConf10 more lessons learned from building Machine Learning systems - MLConf
10 more lessons learned from building Machine Learning systems - MLConf
 
10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems10 more lessons learned from building Machine Learning systems
10 more lessons learned from building Machine Learning systems
 
Machine Learning to Grow the World's Knowledge
Machine Learning to Grow  the World's KnowledgeMachine Learning to Grow  the World's Knowledge
Machine Learning to Grow the World's Knowledge
 
MLConf Seattle 2015 - ML@Quora
MLConf Seattle 2015 - ML@QuoraMLConf Seattle 2015 - ML@Quora
MLConf Seattle 2015 - ML@Quora
 
Lean DevOps - Lessons Learned from Innovation-driven Companies
Lean DevOps - Lessons Learned from Innovation-driven CompaniesLean DevOps - Lessons Learned from Innovation-driven Companies
Lean DevOps - Lessons Learned from Innovation-driven Companies
 
10 Lessons Learned from Building Machine Learning Systems
10 Lessons Learned from Building Machine Learning Systems10 Lessons Learned from Building Machine Learning Systems
10 Lessons Learned from Building Machine Learning Systems
 
Recsys 2014 Tutorial - The Recommender Problem Revisited
Recsys 2014 Tutorial - The Recommender Problem RevisitedRecsys 2014 Tutorial - The Recommender Problem Revisited
Recsys 2014 Tutorial - The Recommender Problem Revisited
 
Kdd 2014 Tutorial - the recommender problem revisited
Kdd 2014 Tutorial -  the recommender problem revisitedKdd 2014 Tutorial -  the recommender problem revisited
Kdd 2014 Tutorial - the recommender problem revisited
 

Recently uploaded

Diseases of the Respiratory System (J00-J99),.pptx
Diseases of the Respiratory System (J00-J99),.pptxDiseases of the Respiratory System (J00-J99),.pptx
Diseases of the Respiratory System (J00-J99),.pptxEMADABATHINI PRABHU TEJA
 
Artificial Intelligence in Healthcare: Challenges, Risks, Benefits
Artificial Intelligence in Healthcare: Challenges, Risks, BenefitsArtificial Intelligence in Healthcare: Challenges, Risks, Benefits
Artificial Intelligence in Healthcare: Challenges, Risks, BenefitsIris Thiele Isip-Tan
 
Living Well Every Day: Lyons Wellness Practice | Nurtures Your Complete Health
Living Well Every Day: Lyons Wellness Practice | Nurtures Your Complete HealthLiving Well Every Day: Lyons Wellness Practice | Nurtures Your Complete Health
Living Well Every Day: Lyons Wellness Practice | Nurtures Your Complete HealthLyons Health
 
FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES 11
FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES  11FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES  11
FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES 11crzljavier
 
"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf
"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf
"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdfDolisha Warbi
 
Basics of Giant Cell Tumor of bone (GCTB)
Basics of Giant Cell Tumor of bone (GCTB)Basics of Giant Cell Tumor of bone (GCTB)
Basics of Giant Cell Tumor of bone (GCTB)bishwabandhuniraula
 
Assisted Living Care Residency - PapayaCare
Assisted Living Care Residency - PapayaCareAssisted Living Care Residency - PapayaCare
Assisted Living Care Residency - PapayaCareratilalthakkar704
 
Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....
Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....
Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....sharyurangari111
 
Medical Malpractice & Medical Negligence (1).pptx
Medical Malpractice & Medical Negligence (1).pptxMedical Malpractice & Medical Negligence (1).pptx
Medical Malpractice & Medical Negligence (1).pptxanukshadias2
 
Calibration and Calibration Curve. lecture notes
Calibration and Calibration Curve. lecture notesCalibration and Calibration Curve. lecture notes
Calibration and Calibration Curve. lecture notesWani Insha
 
Experience the Power of Chiropractic in Maui
Experience the Power of Chiropractic in MauiExperience the Power of Chiropractic in Maui
Experience the Power of Chiropractic in MauiCentral Maui Chiropractic
 
TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...
TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...
TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...mwangimwangi222
 
ACCA Version of AI & Healthcare: An Overview for the Curious
ACCA Version of AI & Healthcare: An Overview for the CuriousACCA Version of AI & Healthcare: An Overview for the Curious
ACCA Version of AI & Healthcare: An Overview for the CuriousKR_Barker
 
LARYNGEAL CANCER.pptx Prepared by Neha Kewat
LARYNGEAL CANCER.pptx  Prepared by Neha KewatLARYNGEAL CANCER.pptx  Prepared by Neha Kewat
LARYNGEAL CANCER.pptx Prepared by Neha KewatNehaKewat
 
LEUKODYSTROPHY FINAL.pptx sms medical jaipur
LEUKODYSTROPHY FINAL.pptx sms medical jaipurLEUKODYSTROPHY FINAL.pptx sms medical jaipur
LEUKODYSTROPHY FINAL.pptx sms medical jaipurdineshdandia
 
Presentation on COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSING
Presentation on  COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSINGPresentation on  COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSING
Presentation on COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSINGKREDASONBANGALORE
 
Introduction to Evaluation and Skin Benefits
Introduction to Evaluation and Skin BenefitsIntroduction to Evaluation and Skin Benefits
Introduction to Evaluation and Skin Benefitssahilgabhane29
 

Recently uploaded (20)

Diseases of the Respiratory System (J00-J99),.pptx
Diseases of the Respiratory System (J00-J99),.pptxDiseases of the Respiratory System (J00-J99),.pptx
Diseases of the Respiratory System (J00-J99),.pptx
 
Artificial Intelligence in Healthcare: Challenges, Risks, Benefits
Artificial Intelligence in Healthcare: Challenges, Risks, BenefitsArtificial Intelligence in Healthcare: Challenges, Risks, Benefits
Artificial Intelligence in Healthcare: Challenges, Risks, Benefits
 
Living Well Every Day: Lyons Wellness Practice | Nurtures Your Complete Health
Living Well Every Day: Lyons Wellness Practice | Nurtures Your Complete HealthLiving Well Every Day: Lyons Wellness Practice | Nurtures Your Complete Health
Living Well Every Day: Lyons Wellness Practice | Nurtures Your Complete Health
 
FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES 11
FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES  11FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES  11
FINAL PROJECT IN EMPOWERMENT TECHNOLOGIES 11
 
Annual Training
Annual TrainingAnnual Training
Annual Training
 
"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf
"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf
"ANATOMY AND PHYSIOLOGY OF THE SKIN".pdf
 
Basics of Giant Cell Tumor of bone (GCTB)
Basics of Giant Cell Tumor of bone (GCTB)Basics of Giant Cell Tumor of bone (GCTB)
Basics of Giant Cell Tumor of bone (GCTB)
 
Assisted Living Care Residency - PapayaCare
Assisted Living Care Residency - PapayaCareAssisted Living Care Residency - PapayaCare
Assisted Living Care Residency - PapayaCare
 
Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....
Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....
Toothpaste for bleeding gums and sensitive teeth. Teeth whitening, Mouthwash....
 
Medical Malpractice & Medical Negligence (1).pptx
Medical Malpractice & Medical Negligence (1).pptxMedical Malpractice & Medical Negligence (1).pptx
Medical Malpractice & Medical Negligence (1).pptx
 
Calibration and Calibration Curve. lecture notes
Calibration and Calibration Curve. lecture notesCalibration and Calibration Curve. lecture notes
Calibration and Calibration Curve. lecture notes
 
Experience the Power of Chiropractic in Maui
Experience the Power of Chiropractic in MauiExperience the Power of Chiropractic in Maui
Experience the Power of Chiropractic in Maui
 
TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...
TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...
TEST BANK For Neonatal and Pediatric Respiratory Care, 6th Edition by Brian K...
 
ACCA Version of AI & Healthcare: An Overview for the Curious
ACCA Version of AI & Healthcare: An Overview for the CuriousACCA Version of AI & Healthcare: An Overview for the Curious
ACCA Version of AI & Healthcare: An Overview for the Curious
 
LARYNGEAL CANCER.pptx Prepared by Neha Kewat
LARYNGEAL CANCER.pptx  Prepared by Neha KewatLARYNGEAL CANCER.pptx  Prepared by Neha Kewat
LARYNGEAL CANCER.pptx Prepared by Neha Kewat
 
LEUKODYSTROPHY FINAL.pptx sms medical jaipur
LEUKODYSTROPHY FINAL.pptx sms medical jaipurLEUKODYSTROPHY FINAL.pptx sms medical jaipur
LEUKODYSTROPHY FINAL.pptx sms medical jaipur
 
Painting Rats White Angers Them to No End
Painting Rats White Angers Them to No EndPainting Rats White Angers Them to No End
Painting Rats White Angers Them to No End
 
SCOPE OF CRITICAL CARE ORGANIZATION
SCOPE OF CRITICAL CARE ORGANIZATIONSCOPE OF CRITICAL CARE ORGANIZATION
SCOPE OF CRITICAL CARE ORGANIZATION
 
Presentation on COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSING
Presentation on  COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSINGPresentation on  COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSING
Presentation on COUNSELING. 1ST YEAR GNM ,COMMUNITY HEALTH NURSING
 
Introduction to Evaluation and Skin Benefits
Introduction to Evaluation and Skin BenefitsIntroduction to Evaluation and Skin Benefits
Introduction to Evaluation and Skin Benefits
 

AI for COVID-19: An online virtual care approach

  • 1. AI for COVID-19: An online virtual care approach X. Amatriain, PhD Geoff Tso, MD Anitha Kannan, PhD COVID-19 and AI Virtual Conference Stanford 04/01/2020
  • 3. ● >50% world with no access to essential health services ○ ~30% of US adults under-insured ● ~15 min. to capture information, diagnose, recommend treatment ● ⅓ of Americans self-diagnose online Healthcare access and scalability shortage of 120,000 physicians by 2030
  • 4. Towards AI powered scalable health systems ● Mobile-First Care, always on, accessible, affordable ● AI + human providers in the loop for quality care ● Always-Learning system ● AI to operate in-the-wild (EHR)
  • 5. How does this look like?
  • 6. Our approach to COVID-19
  • 8. AI + Providers in the loop + Daily follow up
  • 9. Working on... ● Added at-home testing capabilities to our platform, waiting for FDA to approve ● In discussions with existing health systems who may use platform to scale and improve access
  • 11. Question similarity ● Transfer learning ● Double-finetune BERT model ● Handle data sparsity ● Medical domain knowledge through an intermediate QA binary task ● Out-of-the-box applied to COVID specific Q/A BERT pre-trained weights BERT question Label Loss answer BERT Q Label Loss Q QA
  • 12. Automated Question/Answering User Questions Matching Questions in our FAQ (Answer not shown here for brevity) When do COVID symptoms start after exposure? How long is it between when a person is exposed to the virus and when they start showing symptoms? I am asymptomatic and have been social distancing/self-isolating for the past x days. Can I still transmit the infection? How can someone pass along coronavirus when asymptomatic? If not sneezing or coughing, how can they infect others? Currently I’m experiencing a cough and slight chest pain. Should I just stay at home? At what point will I know I have to go to the ER? When should you go to the emergency room? ● Automated question answering via question similarity ● Practitioners’ vetted answers with ability to follow up
  • 13. ML + Expert systems for Dx models female middle aged fever cough Influenza 16.9 bacterial pneumonia 16.9 acute sinusitis 10.9 asthma 10.9 common cold 10.9 influenza 0.753 bacterial pneumonia 0.205 asthma 0.017 acute sinusitis 0.008 pulmonary tuberculosis 0.007 Inputs DDx with expert systems DDx with ML model Expert system Clinical case simulator Clinical cases DDx ML model Common cold UTI Acute bronchitis Female Middle-aged Chronic cough Nasal congestion Other data (e.g. EHR)
  • 14. Feedback loop Inputs DDx before COVID DDx after COVID female middle aged fever cough healthcare worker influenza 0.753 bacterial pneumonia 0.205 asthma 0.017 acute sinusitis 0.008 pulmonary tuberculosis 0.007 COVID-19 0.913 influenza 0.048 bacterial pneumonia 0.024 pulmonary tuberculosis 0.004 adenovirus infection 0.003 female middle aged fever cough nasal congestion influenza 0.634 adenovirus infection 0.159 bacterial pneumonia 0.114 acute sinusitis 0.05 asthma 0.019 influenza 0.512 COVID-19 0.256 adenovirus infection 0.106 bacterial pneumonia 0.069 acute sinusitis 0.026
  • 15. Conclusions ● Healthcare needs to scale quickly, and this has become obvious in a global pandemic like the one we are facing ● The only way to scale healthcare while improving quality and accessibility is through technology and AI ● AI cannot be simply “dropped” in the middle of old workflows and approaches ○ It needs to be integrated in end-to-end medical care benefitting both patients and providers