SlideShare a Scribd company logo
Enabling Precision
Health with Edison AI
Sandeep Lakshmipathy
GEHealthcare.com
Sandeep Lakshmipathy
Director of Engineering, Edison AI
GE Healthcare
With close to 2 decades in the software industry, and the last 7 years in the Healthcare domain,
Sandeep has played diverse roles in Technology & Product Management space. Sandeep is
currently the Director of Software for Edison AI Platform at GE Healthcare in the John F Welch
Technology Center in Bengaluru, India. Sandeep leads several initiatives to accelerate AI product
development across the healthcare products.
2
3
40% shortage
in practicing obstetrics/
gynecology doctors
2.1 nurse/midwife
.8 doctor
.6 obstetrics/gynecology
doctor
Per 1,000 people in India
Prevalence Stats: https://data.worldbank.org/indicator/SH.MED.NUMW.P3
Occurrence of CNS: Occurance of CNS abnormalities: http://www.ijmr.org.in/temp/IndianJMedRes1454471-5575188_152911.pdf
Shortage of practicing obstetrics/gynecology doctors: https://indianexpress.com/article/india/india-others/paediatrics-to-gynae-where-are-the-surgeons-physicians/
Ultrasound is highly user
dependent, repetitious, and
manual.
Clinical training is often
neglected
~130M babies born
every year
~350K babies born
every day
Healthcare Challenges
4
Healthcare Artificial Intelligence
An infinite AI space
■ Physics
■ Anatomy
■ Function (fMR)
■ Pre/intra/post scan
■ Genomics
■ And more
https://wsrs.org/2018meeting/handouts/allen_ai.pdf
5
TRAININGEST ANNOTATE
DEPLOYMENT
TARGETS
HOSPITAL
PARTNERS
AWS
IAM
AMAZON
COGNITO
AMAZON
CLOUDWATCH
AMAZON
S3
AMAZON
EC2
GE HEALTH
CLOUD
GE HEALTH CLOUD
EDGE
TRAININGEST ANNOTATE
GE HEALTH CLOUD
FEEDBACK
Edison | An Artificial Intelligence
Factory for Everyone
Cloud Platform for GEHC Internal AI Model Development / Deployment
AWS Cloud
We like the Edison AI
Cloud Workbench,
but can we have this
on-prem ?
6
TRAININGEST ANNOTATE
DEPLOYMENT
TARGETS
HOSPITAL
PARTNERS
AWS
IAM
AMAZON
COGNITO
AMAZON
CLOUDWATCH
AMAZON
S3
AMAZON
EC2
GE HEALTH
CLOUD
EDISON HEALTHLINK (On-Prem)
EDGE
TRAININGEST ANNOTATE
On-Prem
FEEDBACK
On-Prem Deployment of Edison AI Workbench for Research Purposes
Scylla Alternator
Edison | An Artificial Intelligence
Factory for Everyone
Edison AI Workbench
Multiple Deployment Options
7https://wsrs.org/2018meeting/handouts/allen_ai.pdf
Edison AI Workbench | Cloud
Edison AI Workbench | On-Prem
On Edison Platform Hardware
Zeroing in on Scylla Alternator
▪ Porting cloud asset to run on-prem is non-trivial
▪ People expertise & Time to market considerations
▪ Wanted to minimize turn-around time for ISO releases
▪ Keeping DB layer similar across cloud & on-prem was
invaluable for our use-case
▪ API compatibility with DynamoDB was need of the hour
▪ Quick proof-of-concepts helped decision making
▪ Also K8s compatibility accelerated deployment
8
Support from ScyllaDB Team
Always Available
▪ Developer level interactions
▪ Quick turn-around with
nightly builds for issue fixes
▪ Constant touch-bases from
Technical & Marketing
teams
9
Receptivity & Flexibility
▪ Around DynamoDB Streams
▪ Customized licensing for
our needs
▪ Partnering in solution
evolution
Having Right Data
Our experience on volume
10
Essential, but not sufficient
■ Volume increases performance
■ Volume must be “balanced”
■ Annotation can drive volume
needs
Supporting on-prem AI
Workbench needs allows
access to data that cannot
get onto cloud for variety of
reasons!
Variety prevents brittle
Artificial Intelligence
■ DL models are data driven
■ If only one data source is used, the
model is likely “brittle” and not
generalizable
■ Diversity = geo, depart, vendor,
socio/eco, and more
11
GEHealthcare.com
© 2019 General Electric Company – All rights reserved.
GE Healthcare reserves the right to make changes in specifications and features shown herein, or discontinue the product described at any time without notice or obligation. Contact your GE Healthcare
representative for the most current information. GE Medical Systems, Inc., doing business as GE Healthcare. GE Healthcare, a division of General Electric Company. GE and the GE Monogram are
trademarks of GE Electric Company.
Conclusion
Partnerships will be key to AI Revolution
Thank You
@sandeepl
sandeep.lakshmipathy@ge.com
Sandeep Lakshmipathy

More Related Content

What's hot

The Vision & Challenge of Applied Machine Learning
The Vision & Challenge of Applied Machine LearningThe Vision & Challenge of Applied Machine Learning
The Vision & Challenge of Applied Machine Learning
Cloudera, Inc.
 
Troubleshooting your elasticsearch cluster like a support engineer
Troubleshooting your elasticsearch cluster like a support engineerTroubleshooting your elasticsearch cluster like a support engineer
Troubleshooting your elasticsearch cluster like a support engineer
Imma Valls Bernaus
 
Scaling Online ML Predictions At DoorDash
Scaling Online ML Predictions At DoorDashScaling Online ML Predictions At DoorDash
Scaling Online ML Predictions At DoorDash
Databricks
 
DOES SFO 2016 - Avan Mathur - Planning for Huge Scale
DOES SFO 2016 - Avan Mathur - Planning for Huge ScaleDOES SFO 2016 - Avan Mathur - Planning for Huge Scale
DOES SFO 2016 - Avan Mathur - Planning for Huge Scale
Gene Kim
 
Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...
Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...
Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...
Databricks
 
Prescriptive Analytics For Apache Cloudstack by ActOnMagic
Prescriptive Analytics For Apache Cloudstack by ActOnMagicPrescriptive Analytics For Apache Cloudstack by ActOnMagic
Prescriptive Analytics For Apache Cloudstack by ActOnMagic
Madan Ganesh Velayudham
 
Cost Effectively Run Multiple Oracle Database Copies at Scale
Cost Effectively Run Multiple Oracle Database Copies at Scale Cost Effectively Run Multiple Oracle Database Copies at Scale
Cost Effectively Run Multiple Oracle Database Copies at Scale
NetApp
 
Webinar: 2 Billion Data Points Each Day
Webinar: 2 Billion Data Points Each DayWebinar: 2 Billion Data Points Each Day
Webinar: 2 Billion Data Points Each Day
DataStax
 
Hadoop Hadoop & Spark meetup - Altiscale
Hadoop Hadoop & Spark meetup - AltiscaleHadoop Hadoop & Spark meetup - Altiscale
Hadoop Hadoop & Spark meetup - Altiscale
Mark Kerzner
 
6 GigaSpaces Principles to Survive Black Friday
6 GigaSpaces Principles to Survive Black Friday6 GigaSpaces Principles to Survive Black Friday
6 GigaSpaces Principles to Survive Black Friday
Ali Hodroj
 
Rounds tips & tricks
Rounds tips & tricksRounds tips & tricks
Rounds tips & tricks
Aviv Laufer
 
[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...
[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...
[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...
Deiser
 
RightScale Webinar: Enterprise-Grade Cloud Cost Planning and Management
RightScale Webinar: Enterprise-Grade Cloud Cost Planning and ManagementRightScale Webinar: Enterprise-Grade Cloud Cost Planning and Management
RightScale Webinar: Enterprise-Grade Cloud Cost Planning and Management
RightScale
 
Rounds analytics pipeline
Rounds analytics pipelineRounds analytics pipeline
Rounds analytics pipeline
Aviv Laufer
 
7 ways for data teams to save money in azure
7 ways for data teams to save money in azure7 ways for data teams to save money in azure
7 ways for data teams to save money in azure
John McCormack
 
Deploy a Scalable Website
Deploy a Scalable WebsiteDeploy a Scalable Website
Deploy a Scalable Website
RightScale
 
High Performance No+SQL for Mission-critical Applications
High Performance No+SQL for Mission-critical ApplicationsHigh Performance No+SQL for Mission-critical Applications
High Performance No+SQL for Mission-critical Applications
FairCom
 
[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio
[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio
[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio
Deiser
 
Introduction to Big Data Technologies: Hadoop/EMR/Map Reduce & Redshift
Introduction to Big Data Technologies:  Hadoop/EMR/Map Reduce & RedshiftIntroduction to Big Data Technologies:  Hadoop/EMR/Map Reduce & Redshift
Introduction to Big Data Technologies: Hadoop/EMR/Map Reduce & Redshift
DataKitchen
 
Journey to cloud openstack nexus ipma 2013
Journey to cloud openstack nexus ipma 2013Journey to cloud openstack nexus ipma 2013
Journey to cloud openstack nexus ipma 2013
Colin McNamara
 

What's hot (20)

The Vision & Challenge of Applied Machine Learning
The Vision & Challenge of Applied Machine LearningThe Vision & Challenge of Applied Machine Learning
The Vision & Challenge of Applied Machine Learning
 
Troubleshooting your elasticsearch cluster like a support engineer
Troubleshooting your elasticsearch cluster like a support engineerTroubleshooting your elasticsearch cluster like a support engineer
Troubleshooting your elasticsearch cluster like a support engineer
 
Scaling Online ML Predictions At DoorDash
Scaling Online ML Predictions At DoorDashScaling Online ML Predictions At DoorDash
Scaling Online ML Predictions At DoorDash
 
DOES SFO 2016 - Avan Mathur - Planning for Huge Scale
DOES SFO 2016 - Avan Mathur - Planning for Huge ScaleDOES SFO 2016 - Avan Mathur - Planning for Huge Scale
DOES SFO 2016 - Avan Mathur - Planning for Huge Scale
 
Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...
Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...
Scale and Optimize Data Engineering Pipelines with Software Engineering Best ...
 
Prescriptive Analytics For Apache Cloudstack by ActOnMagic
Prescriptive Analytics For Apache Cloudstack by ActOnMagicPrescriptive Analytics For Apache Cloudstack by ActOnMagic
Prescriptive Analytics For Apache Cloudstack by ActOnMagic
 
Cost Effectively Run Multiple Oracle Database Copies at Scale
Cost Effectively Run Multiple Oracle Database Copies at Scale Cost Effectively Run Multiple Oracle Database Copies at Scale
Cost Effectively Run Multiple Oracle Database Copies at Scale
 
Webinar: 2 Billion Data Points Each Day
Webinar: 2 Billion Data Points Each DayWebinar: 2 Billion Data Points Each Day
Webinar: 2 Billion Data Points Each Day
 
Hadoop Hadoop & Spark meetup - Altiscale
Hadoop Hadoop & Spark meetup - AltiscaleHadoop Hadoop & Spark meetup - Altiscale
Hadoop Hadoop & Spark meetup - Altiscale
 
6 GigaSpaces Principles to Survive Black Friday
6 GigaSpaces Principles to Survive Black Friday6 GigaSpaces Principles to Survive Black Friday
6 GigaSpaces Principles to Survive Black Friday
 
Rounds tips & tricks
Rounds tips & tricksRounds tips & tricks
Rounds tips & tricks
 
[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...
[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...
[DEISER Talks] "Atlassian Data Center: Deployment Tips & Tricks"- Carlos Apar...
 
RightScale Webinar: Enterprise-Grade Cloud Cost Planning and Management
RightScale Webinar: Enterprise-Grade Cloud Cost Planning and ManagementRightScale Webinar: Enterprise-Grade Cloud Cost Planning and Management
RightScale Webinar: Enterprise-Grade Cloud Cost Planning and Management
 
Rounds analytics pipeline
Rounds analytics pipelineRounds analytics pipeline
Rounds analytics pipeline
 
7 ways for data teams to save money in azure
7 ways for data teams to save money in azure7 ways for data teams to save money in azure
7 ways for data teams to save money in azure
 
Deploy a Scalable Website
Deploy a Scalable WebsiteDeploy a Scalable Website
Deploy a Scalable Website
 
High Performance No+SQL for Mission-critical Applications
High Performance No+SQL for Mission-critical ApplicationsHigh Performance No+SQL for Mission-critical Applications
High Performance No+SQL for Mission-critical Applications
 
[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio
[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio
[DEISER Talks] "Atlassian Data Center: De la A a la Z" - Carlos Aparicio
 
Introduction to Big Data Technologies: Hadoop/EMR/Map Reduce & Redshift
Introduction to Big Data Technologies:  Hadoop/EMR/Map Reduce & RedshiftIntroduction to Big Data Technologies:  Hadoop/EMR/Map Reduce & Redshift
Introduction to Big Data Technologies: Hadoop/EMR/Map Reduce & Redshift
 
Journey to cloud openstack nexus ipma 2013
Journey to cloud openstack nexus ipma 2013Journey to cloud openstack nexus ipma 2013
Journey to cloud openstack nexus ipma 2013
 

Similar to Enabling Precision Health in Edison AI

‘The Valai’ – Our IT Solutions and Services
‘The Valai’ – Our IT Solutions and Services‘The Valai’ – Our IT Solutions and Services
‘The Valai’ – Our IT Solutions and Services
Maan21
 
Top 10 tredning technologies to learn in 2021
Top 10 tredning technologies to learn in 2021Top 10 tredning technologies to learn in 2021
Top 10 tredning technologies to learn in 2021
Lokesh Agarwal
 
Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...
Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...
Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...
NetworkCollaborators
 
Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...
Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...
Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...
Ajay Gangakhedkar
 
[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례
[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례
[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례
kosena
 
Strata dz
Strata dzStrata dz
Strata dz
Anant Jhingran
 
Tdwi austin simplifying big data delivery to drive new insights final
Tdwi austin   simplifying big data delivery to drive new insights finalTdwi austin   simplifying big data delivery to drive new insights final
Tdwi austin simplifying big data delivery to drive new insights final
Sal Marcus
 
Vipul shah intel it transformation an imperative for driving business outcomes
Vipul shah  intel it transformation an imperative for driving business outcomesVipul shah  intel it transformation an imperative for driving business outcomes
Vipul shah intel it transformation an imperative for driving business outcomes
NetworkCollaborators
 
[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...
[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...
[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...
Nur Shiqim Chok
 
[Cisco Connect 2018 - Vietnam] Vipul shah intel it transformation an imperat...
[Cisco Connect 2018 - Vietnam] Vipul shah  intel it transformation an imperat...[Cisco Connect 2018 - Vietnam] Vipul shah  intel it transformation an imperat...
[Cisco Connect 2018 - Vietnam] Vipul shah intel it transformation an imperat...
Nur Shiqim Chok
 
Insync 10 session jd edwards strategy and roadmap anz (a4) - final
Insync 10 session   jd edwards strategy and roadmap anz (a4) - finalInsync 10 session   jd edwards strategy and roadmap anz (a4) - final
Insync 10 session jd edwards strategy and roadmap anz (a4) - final
InSync Conference
 
Maximising likelihood of success: Applying Product Management to AI/ML/DS pr...
Maximising likelihood of success:  Applying Product Management to AI/ML/DS pr...Maximising likelihood of success:  Applying Product Management to AI/ML/DS pr...
Maximising likelihood of success: Applying Product Management to AI/ML/DS pr...
Kevin Wong
 
Healthcare Mobility Consulting and Solution Provider
Healthcare Mobility Consulting and Solution ProviderHealthcare Mobility Consulting and Solution Provider
Healthcare Mobility Consulting and Solution Provider
TVS Next
 
Software Industry
Software Industry Software Industry
Software Industry
polipellyyashaswi
 
Making Hadoop Ready for the Enterprise
Making Hadoop Ready for the Enterprise Making Hadoop Ready for the Enterprise
Making Hadoop Ready for the Enterprise
DataWorks Summit
 
Sivagama_sundari_Sakthivel_Resume_2016
Sivagama_sundari_Sakthivel_Resume_2016Sivagama_sundari_Sakthivel_Resume_2016
Sivagama_sundari_Sakthivel_Resume_2016
sivagama sundari sakthivel
 
Top 10 trending technologies must learn in 2021
Top 10 trending technologies must learn in 2021Top 10 trending technologies must learn in 2021
Top 10 trending technologies must learn in 2021
Nikhilsharma1159
 
ABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG AxisbankABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG Axisbank
Abhijeet Ghag
 
Ravi Sundriyal
Ravi SundriyalRavi Sundriyal
Ravi Sundriyal
Ravi Gaucho
 
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTXCustomer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
tsigitnist02
 

Similar to Enabling Precision Health in Edison AI (20)

‘The Valai’ – Our IT Solutions and Services
‘The Valai’ – Our IT Solutions and Services‘The Valai’ – Our IT Solutions and Services
‘The Valai’ – Our IT Solutions and Services
 
Top 10 tredning technologies to learn in 2021
Top 10 tredning technologies to learn in 2021Top 10 tredning technologies to learn in 2021
Top 10 tredning technologies to learn in 2021
 
Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...
Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...
Cisco Connect 2018 Malaysia - It transformation-an imperative for driving bus...
 
Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...
Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...
Presentation - Aspen - The Untold Benefitsof a Digital Maintenance Strategy f...
 
[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례
[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례
[코세나, kosena] Auto ML, H2O.ai의 제조분야 AI 활용 사례
 
Strata dz
Strata dzStrata dz
Strata dz
 
Tdwi austin simplifying big data delivery to drive new insights final
Tdwi austin   simplifying big data delivery to drive new insights finalTdwi austin   simplifying big data delivery to drive new insights final
Tdwi austin simplifying big data delivery to drive new insights final
 
Vipul shah intel it transformation an imperative for driving business outcomes
Vipul shah  intel it transformation an imperative for driving business outcomesVipul shah  intel it transformation an imperative for driving business outcomes
Vipul shah intel it transformation an imperative for driving business outcomes
 
[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...
[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...
[Cisco Connect 2018 - Vietnam] It transformation an imperative for driving bu...
 
[Cisco Connect 2018 - Vietnam] Vipul shah intel it transformation an imperat...
[Cisco Connect 2018 - Vietnam] Vipul shah  intel it transformation an imperat...[Cisco Connect 2018 - Vietnam] Vipul shah  intel it transformation an imperat...
[Cisco Connect 2018 - Vietnam] Vipul shah intel it transformation an imperat...
 
Insync 10 session jd edwards strategy and roadmap anz (a4) - final
Insync 10 session   jd edwards strategy and roadmap anz (a4) - finalInsync 10 session   jd edwards strategy and roadmap anz (a4) - final
Insync 10 session jd edwards strategy and roadmap anz (a4) - final
 
Maximising likelihood of success: Applying Product Management to AI/ML/DS pr...
Maximising likelihood of success:  Applying Product Management to AI/ML/DS pr...Maximising likelihood of success:  Applying Product Management to AI/ML/DS pr...
Maximising likelihood of success: Applying Product Management to AI/ML/DS pr...
 
Healthcare Mobility Consulting and Solution Provider
Healthcare Mobility Consulting and Solution ProviderHealthcare Mobility Consulting and Solution Provider
Healthcare Mobility Consulting and Solution Provider
 
Software Industry
Software Industry Software Industry
Software Industry
 
Making Hadoop Ready for the Enterprise
Making Hadoop Ready for the Enterprise Making Hadoop Ready for the Enterprise
Making Hadoop Ready for the Enterprise
 
Sivagama_sundari_Sakthivel_Resume_2016
Sivagama_sundari_Sakthivel_Resume_2016Sivagama_sundari_Sakthivel_Resume_2016
Sivagama_sundari_Sakthivel_Resume_2016
 
Top 10 trending technologies must learn in 2021
Top 10 trending technologies must learn in 2021Top 10 trending technologies must learn in 2021
Top 10 trending technologies must learn in 2021
 
ABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG AxisbankABHIJEET MURLIDHAR GHAG Axisbank
ABHIJEET MURLIDHAR GHAG Axisbank
 
Ravi Sundriyal
Ravi SundriyalRavi Sundriyal
Ravi Sundriyal
 
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTXCustomer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
 

More from ScyllaDB

Optimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through ObservabilityOptimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through Observability
ScyllaDB
 
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream ProcessingEvent-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream Processing
ScyllaDB
 
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
ScyllaDB
 
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
ScyllaDB
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
ScyllaDB
 
What Developers Need to Unlearn for High Performance NoSQL
What Developers Need to Unlearn for High Performance NoSQLWhat Developers Need to Unlearn for High Performance NoSQL
What Developers Need to Unlearn for High Performance NoSQL
ScyllaDB
 
Low Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & PitfallsLow Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & Pitfalls
ScyllaDB
 
Dissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance DilemmasDissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance Dilemmas
ScyllaDB
 
Beyond Linear Scaling: A New Path for Performance with ScyllaDB
Beyond Linear Scaling: A New Path for Performance with ScyllaDBBeyond Linear Scaling: A New Path for Performance with ScyllaDB
Beyond Linear Scaling: A New Path for Performance with ScyllaDB
ScyllaDB
 
Dissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance DilemmasDissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance Dilemmas
ScyllaDB
 
Database Performance at Scale Masterclass: Workload Characteristics by Felipe...
Database Performance at Scale Masterclass: Workload Characteristics by Felipe...Database Performance at Scale Masterclass: Workload Characteristics by Felipe...
Database Performance at Scale Masterclass: Workload Characteristics by Felipe...
ScyllaDB
 
Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...
Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...
Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...
ScyllaDB
 
Database Performance at Scale Masterclass: Driver Strategies by Piotr Sarna
Database Performance at Scale Masterclass: Driver Strategies by Piotr SarnaDatabase Performance at Scale Masterclass: Driver Strategies by Piotr Sarna
Database Performance at Scale Masterclass: Driver Strategies by Piotr Sarna
ScyllaDB
 
Replacing Your Cache with ScyllaDB
Replacing Your Cache with ScyllaDBReplacing Your Cache with ScyllaDB
Replacing Your Cache with ScyllaDB
ScyllaDB
 
Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability
Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear ScalabilityPowering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability
Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability
ScyllaDB
 
7 Reasons Not to Put an External Cache in Front of Your Database.pptx
7 Reasons Not to Put an External Cache in Front of Your Database.pptx7 Reasons Not to Put an External Cache in Front of Your Database.pptx
7 Reasons Not to Put an External Cache in Front of Your Database.pptx
ScyllaDB
 
Getting the most out of ScyllaDB
Getting the most out of ScyllaDBGetting the most out of ScyllaDB
Getting the most out of ScyllaDB
ScyllaDB
 
NoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration
NoSQL Database Migration Masterclass - Session 2: The Anatomy of a MigrationNoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration
NoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration
ScyllaDB
 
NoSQL Database Migration Masterclass - Session 3: Migration Logistics
NoSQL Database Migration Masterclass - Session 3: Migration LogisticsNoSQL Database Migration Masterclass - Session 3: Migration Logistics
NoSQL Database Migration Masterclass - Session 3: Migration Logistics
ScyllaDB
 
NoSQL Data Migration Masterclass - Session 1 Migration Strategies and Challenges
NoSQL Data Migration Masterclass - Session 1 Migration Strategies and ChallengesNoSQL Data Migration Masterclass - Session 1 Migration Strategies and Challenges
NoSQL Data Migration Masterclass - Session 1 Migration Strategies and Challenges
ScyllaDB
 

More from ScyllaDB (20)

Optimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through ObservabilityOptimizing NoSQL Performance Through Observability
Optimizing NoSQL Performance Through Observability
 
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream ProcessingEvent-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream Processing
 
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
 
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
What Developers Need to Unlearn for High Performance NoSQL
What Developers Need to Unlearn for High Performance NoSQLWhat Developers Need to Unlearn for High Performance NoSQL
What Developers Need to Unlearn for High Performance NoSQL
 
Low Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & PitfallsLow Latency at Extreme Scale: Proven Practices & Pitfalls
Low Latency at Extreme Scale: Proven Practices & Pitfalls
 
Dissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance DilemmasDissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance Dilemmas
 
Beyond Linear Scaling: A New Path for Performance with ScyllaDB
Beyond Linear Scaling: A New Path for Performance with ScyllaDBBeyond Linear Scaling: A New Path for Performance with ScyllaDB
Beyond Linear Scaling: A New Path for Performance with ScyllaDB
 
Dissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance DilemmasDissecting Real-World Database Performance Dilemmas
Dissecting Real-World Database Performance Dilemmas
 
Database Performance at Scale Masterclass: Workload Characteristics by Felipe...
Database Performance at Scale Masterclass: Workload Characteristics by Felipe...Database Performance at Scale Masterclass: Workload Characteristics by Felipe...
Database Performance at Scale Masterclass: Workload Characteristics by Felipe...
 
Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...
Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...
Database Performance at Scale Masterclass: Database Internals by Pavel Emelya...
 
Database Performance at Scale Masterclass: Driver Strategies by Piotr Sarna
Database Performance at Scale Masterclass: Driver Strategies by Piotr SarnaDatabase Performance at Scale Masterclass: Driver Strategies by Piotr Sarna
Database Performance at Scale Masterclass: Driver Strategies by Piotr Sarna
 
Replacing Your Cache with ScyllaDB
Replacing Your Cache with ScyllaDBReplacing Your Cache with ScyllaDB
Replacing Your Cache with ScyllaDB
 
Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability
Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear ScalabilityPowering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability
Powering Real-Time Apps with ScyllaDB_ Low Latency & Linear Scalability
 
7 Reasons Not to Put an External Cache in Front of Your Database.pptx
7 Reasons Not to Put an External Cache in Front of Your Database.pptx7 Reasons Not to Put an External Cache in Front of Your Database.pptx
7 Reasons Not to Put an External Cache in Front of Your Database.pptx
 
Getting the most out of ScyllaDB
Getting the most out of ScyllaDBGetting the most out of ScyllaDB
Getting the most out of ScyllaDB
 
NoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration
NoSQL Database Migration Masterclass - Session 2: The Anatomy of a MigrationNoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration
NoSQL Database Migration Masterclass - Session 2: The Anatomy of a Migration
 
NoSQL Database Migration Masterclass - Session 3: Migration Logistics
NoSQL Database Migration Masterclass - Session 3: Migration LogisticsNoSQL Database Migration Masterclass - Session 3: Migration Logistics
NoSQL Database Migration Masterclass - Session 3: Migration Logistics
 
NoSQL Data Migration Masterclass - Session 1 Migration Strategies and Challenges
NoSQL Data Migration Masterclass - Session 1 Migration Strategies and ChallengesNoSQL Data Migration Masterclass - Session 1 Migration Strategies and Challenges
NoSQL Data Migration Masterclass - Session 1 Migration Strategies and Challenges
 

Recently uploaded

Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Zilliz
 
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
sonjaschweigert1
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
KatiaHIMEUR1
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Safe Software
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
Edge AI and Vision Alliance
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Neo4j
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
ControlCase
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
KAMESHS29
 
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionGenerative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Aggregage
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
Matthew Sinclair
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
James Anderson
 
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
Pixlogix Infotech
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems S.M.S.A.
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Neo4j
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Matthew Sinclair
 

Recently uploaded (20)

Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
Introducing Milvus Lite: Easy-to-Install, Easy-to-Use vector database for you...
 
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
 
Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !Securing your Kubernetes cluster_ a step-by-step guide to success !
Securing your Kubernetes cluster_ a step-by-step guide to success !
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FMEEssentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
PCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase TeamPCI PIN Basics Webinar from the Controlcase Team
PCI PIN Basics Webinar from the Controlcase Team
 
RESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for studentsRESUME BUILDER APPLICATION Project for students
RESUME BUILDER APPLICATION Project for students
 
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionGenerative AI Deep Dive: Advancing from Proof of Concept to Production
Generative AI Deep Dive: Advancing from Proof of Concept to Production
 
20240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 202420240607 QFM018 Elixir Reading List May 2024
20240607 QFM018 Elixir Reading List May 2024
 
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
 
20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website20 Comprehensive Checklist of Designing and Developing a Website
20 Comprehensive Checklist of Designing and Developing a Website
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
 
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
 
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 202420240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
 

Enabling Precision Health in Edison AI

  • 1. Enabling Precision Health with Edison AI Sandeep Lakshmipathy GEHealthcare.com
  • 2. Sandeep Lakshmipathy Director of Engineering, Edison AI GE Healthcare With close to 2 decades in the software industry, and the last 7 years in the Healthcare domain, Sandeep has played diverse roles in Technology & Product Management space. Sandeep is currently the Director of Software for Edison AI Platform at GE Healthcare in the John F Welch Technology Center in Bengaluru, India. Sandeep leads several initiatives to accelerate AI product development across the healthcare products. 2
  • 3. 3 40% shortage in practicing obstetrics/ gynecology doctors 2.1 nurse/midwife .8 doctor .6 obstetrics/gynecology doctor Per 1,000 people in India Prevalence Stats: https://data.worldbank.org/indicator/SH.MED.NUMW.P3 Occurrence of CNS: Occurance of CNS abnormalities: http://www.ijmr.org.in/temp/IndianJMedRes1454471-5575188_152911.pdf Shortage of practicing obstetrics/gynecology doctors: https://indianexpress.com/article/india/india-others/paediatrics-to-gynae-where-are-the-surgeons-physicians/ Ultrasound is highly user dependent, repetitious, and manual. Clinical training is often neglected ~130M babies born every year ~350K babies born every day Healthcare Challenges
  • 4. 4 Healthcare Artificial Intelligence An infinite AI space ■ Physics ■ Anatomy ■ Function (fMR) ■ Pre/intra/post scan ■ Genomics ■ And more https://wsrs.org/2018meeting/handouts/allen_ai.pdf
  • 5. 5 TRAININGEST ANNOTATE DEPLOYMENT TARGETS HOSPITAL PARTNERS AWS IAM AMAZON COGNITO AMAZON CLOUDWATCH AMAZON S3 AMAZON EC2 GE HEALTH CLOUD GE HEALTH CLOUD EDGE TRAININGEST ANNOTATE GE HEALTH CLOUD FEEDBACK Edison | An Artificial Intelligence Factory for Everyone Cloud Platform for GEHC Internal AI Model Development / Deployment AWS Cloud We like the Edison AI Cloud Workbench, but can we have this on-prem ?
  • 6. 6 TRAININGEST ANNOTATE DEPLOYMENT TARGETS HOSPITAL PARTNERS AWS IAM AMAZON COGNITO AMAZON CLOUDWATCH AMAZON S3 AMAZON EC2 GE HEALTH CLOUD EDISON HEALTHLINK (On-Prem) EDGE TRAININGEST ANNOTATE On-Prem FEEDBACK On-Prem Deployment of Edison AI Workbench for Research Purposes Scylla Alternator Edison | An Artificial Intelligence Factory for Everyone
  • 7. Edison AI Workbench Multiple Deployment Options 7https://wsrs.org/2018meeting/handouts/allen_ai.pdf Edison AI Workbench | Cloud Edison AI Workbench | On-Prem On Edison Platform Hardware
  • 8. Zeroing in on Scylla Alternator ▪ Porting cloud asset to run on-prem is non-trivial ▪ People expertise & Time to market considerations ▪ Wanted to minimize turn-around time for ISO releases ▪ Keeping DB layer similar across cloud & on-prem was invaluable for our use-case ▪ API compatibility with DynamoDB was need of the hour ▪ Quick proof-of-concepts helped decision making ▪ Also K8s compatibility accelerated deployment 8
  • 9. Support from ScyllaDB Team Always Available ▪ Developer level interactions ▪ Quick turn-around with nightly builds for issue fixes ▪ Constant touch-bases from Technical & Marketing teams 9 Receptivity & Flexibility ▪ Around DynamoDB Streams ▪ Customized licensing for our needs ▪ Partnering in solution evolution
  • 10. Having Right Data Our experience on volume 10 Essential, but not sufficient ■ Volume increases performance ■ Volume must be “balanced” ■ Annotation can drive volume needs Supporting on-prem AI Workbench needs allows access to data that cannot get onto cloud for variety of reasons! Variety prevents brittle Artificial Intelligence ■ DL models are data driven ■ If only one data source is used, the model is likely “brittle” and not generalizable ■ Diversity = geo, depart, vendor, socio/eco, and more
  • 11. 11 GEHealthcare.com © 2019 General Electric Company – All rights reserved. GE Healthcare reserves the right to make changes in specifications and features shown herein, or discontinue the product described at any time without notice or obligation. Contact your GE Healthcare representative for the most current information. GE Medical Systems, Inc., doing business as GE Healthcare. GE Healthcare, a division of General Electric Company. GE and the GE Monogram are trademarks of GE Electric Company. Conclusion Partnerships will be key to AI Revolution

Editor's Notes

  1. On-Prem Edison AI Workbench available for GEHC research partners only
  2. Our team’s checklists include evaluating the right volume of data for the desired outcome. As good statistics taught us, volume increases predictive accuracies, and balanced volume is critical. Note how the largest data set doesn’t deliver the best outcome, the largest balanced data set does.
  3. Our team’s checklists include evaluating the right volume of data for the desired outcome. As good statistics taught us, volume increases predictive accuracies, and balanced volume is critical. Note how the largest data set doesn’t deliver the best outcome, the largest balanced data set does.