llia Tulchinsky,Engineering Director, Google Cloud Healthcare and Lifesciences

Unlocking Electronic Healthcare & Life Sciences Data

More data was created in the last two years than the previous 5,000 years of humanity.*

*SINTEF. "Big Data, for better or worse: 90% of world's data generated over last two years." ScienceDaily. ScienceDaily, 22 May 2013. sciencedaily.com/releases/2013/05/130522085217

● More plug-and-play layout options

● Full bleed and close-to-full bleed photo layouts

● Slides with product branding

● Slides with a dark background

● Scaled down type overall to allow for more information

● Consistent placement for branding on each slide

● Editable devices for screenshots

● Lots more awesome tweaks based on your feedback!

GGCATGACTA

Traditional Genomics In Home Monitoring

Connected medical devices

Personal Devices & Apps

● EHRS● ICD-10 codes● Clinical Trials

By 2015, genomics data was doubling every 7 months **

● Motion sensors● Smart speakers

Healthcare data is exploding

Data

Analytics and Actionable Insights

Re-engineering and Instrumentation

AI Driven Automation

The goal: data driven enterprise

Big Query

Google CloudHealthcare API

Cloud Machine Learning Engine

Cloud Datalab

Pub Sub

Cloud as a data aggregation platform

GGCATGACTA

DataInsights & Actions

Align and harmonize it into a warehouse

Augment with analytics

Analyze with other data (including cross-modality)

Use it as the basis for machine learning

So you’ve ingested this data into Cloud: Now what?

SecureData encrypted at rest and in motion with fine-grained access control

SimpleAnalyze data from across Google Cloud Platform using SQL

ScalableMulti-petabyte Horizontal scalability, high performance

ShareablePublic and commercial datasets to enhance analysis

Google Cloud Platform’s enterprise data warehouse for analytics

SafeFully-managed service with low TCO

BI/Visualization

BigQuery for scalable analytics

Coded numeric/text

Radiology PACS

FHIR API HL7v2 API

DICOM API

OMICSVariantTransformsGGCATGACTA

Electronic Health Record

Images

Variant, RNASeq, ...

Combine modalities for deep insight

Biomedical Datasets from NIHSTRIDES (Science & Tech Research Infrastructure for Discovery, Experimentation, and Sustainability)

Global Health from The World Bank

Nutrition, reproductive health, education, immunization, and diseases from 200+ countries

RxNorm{ingredient + strength + dose form} for clinical drugs, brand names, and drug classes

Human Variant Annotation DatasetsOriginal NCBI Variant Call Files (VCF) files, NHLBI Exome Sequencing Project (ESP) and ensembl

HCPCS Level II from US Health & Human ServicesBilling codes for ambulance services and supplies used outside a physician’s office

Hospitals registered with MedicareAddresses, hospital types and quality of care for 4000+ Medicare-certified and VA hospitals

CMS Medicare utilization and paymentsProcedures, services, and prescription drugs provided by hospitals, physicians, and others

National Plan and Provider Enumeration SystemNPI, name, speciality, and practice address and FOIA-disclosable health care provider data

Contagious diseasesWeekly surveillance reports by city and state of nationally notifiable diseases from 1888 onwards

100+ public data sets

Keys for success with Machine Learning

ProblemHave a well defined problem with a specific answer

DataNeed a large number of clear examples with consistent answer

SuccessHave a clear success metric. How good is good?

ValueAssuming success according to the metric, what is the value to the business?

IntegrationHow do I integrate the tool into my workflow so that it can be used by the people who need it?

Develop and train your own models

Machine Learning as an API

Cloud Vision API

Cloud Speech API

Cloud Machine Learning Engine

Cloud Translation API

Cloud Natural Language API

Cloud VideoIntelligence

DataFlowDataProc

Hosted Analytics and TensorflowGoogle developed and trained models

Start with a Google modelcustomize with your dataCloud AutoML

Cloud AutoML VisionCloud AutoML NLOthers to Follow

Three ways GCP is bringing ML to the market

More advanced problem?

Try Tensorflow on Cloud Machine Learning Engine

Biomedical Datasets from NIHSTRIDES (Science & Tech Research Infrastructure for Discovery, Experimentation, and Sustainability)

Global Health from The World BankNutrition, reproductive health, education, immunization, and diseases from 200+ countries

RxNorm{ingredient + strength + dose form} for clinical drugs, brand names, and drug classes

Human Variant Annotation DatasetsOriginal NCBI Variant Call Files (VCF) files, NHLBI Exome Sequencing Project (ESP) and ensembl

HCPCS Level II from US Health & Human ServicesBilling codes for ambulance services and supplies used outside a physician’s office

Hospitals registered with MedicareAddresses, hospital types and quality of care for 4000+ Medicare-certified and VA hospitals

CMS Medicare utilization and paymentsProcedures, services, and prescription drugs provided by hospitals, physicians, and others

National Plan and Provider Enumeration SystemNPI, name, speciality, and practice address and FOIA-disclosable health care provider data

Contagious diseasesWeekly surveillance reports by city and state of nationally notifiable diseases from 1888 onwards

100+ public data sets

https://cloud.google.com/healthcare/

https://cloud.google.com/

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healthcare/docs/resources/nih-chest

https://github.com/GoogleCloudPlatform/healthcare/tree/master/imaging/ml_codelab

Healthcare API, datasets, codelabs

Thank you.