CHIPS

Healthcare vs Financial

• Financial
  • Number of accounts: 10,000 to 300 million
  • Storage per Account: GB
  • Total Storage: 10s of TB to 300 PB
• Healthcare
  • Number of patients: 10,000 to 300 million
  • Storage per Patient: GB today, TB tomorrow
  • Total Storage: 20 PB to 600 EB

Healthcare

Healthcare

• 1.65M tumors measured in various modalities
• > 4 exabytes of data in various localities
• 1 petabyte of data (0.001EB) to transfer 
• On current Internet, would take about 21 days to transfer this data around.

healthcare informatics landscape...

Compounding Complexity

• Data is distributed in multiple places
  • EMRs
  • Modality Databases
  • Department databases
  • Different formats
• Data is structured and unstructured
  • "Voice" recordings
  • "Free form text"

Compounding Complexity

• Inconsistent/variable definitions
  • Quantitative interpretations
  • Qualitative measurement variability
    • T(R) on Siemens might be different to GE
• Data itself is complex
  • genomics
  • radiomics (images)
  • combinatorial explosion

Current App Philosophy

• Old-style "web" apps subsumed to look like desktop apps.
  • Reflect an "app" centric model, not "data" centric.
• Not really "web" apps:
  • Typically limited to obsolete versions of Internet Explorer
  • No support for mobile or other platforms.
• No cross-app integration on data level.

silos...

sparse dataverse...

data needs "connectedness"

Current

• Unidirectional
• Isolated
• Non-integrative
• Static

Future

• Multi-directional
• Collaborative
• Integrative
• Dynamic

clouds and clouds and clouds...

what do clouds do?

medical compute... in the cloud

• allows for advanced view rendering
• allows for sharing of images
• allows for immersive real time collaboration
• allows for post-processing of images

pfurl --verb POST --raw --http 172.17.0.2:5055/api/v1/cmd --msg \
'{  "action": "pushPath",
    "meta": {
        "remote": {
            "key":         "someKey"
        },
        "local": {
            "path":         "/home/data"
        },
        "transport": {
            "mechanism":    "compress",
            "compress": {
                "encoding": "base64",
                "archive":  "zip",
                "unpack":   true,
                "cleanup":  true
            }
        }
    }
}' --quiet --jsonpprintindent 4  

pfurl --verb POST --raw --http 172.17.0.2:5010/api/v1/cmd \
     --jsonwrapper 'payload' --msg \
'{  "action": "run",
        "meta": {
                "cmd":      "cal 7 1970",
                "auid":     "rudolphpienaar",
                "jid":      "cal-job-1234",
                "threaded": true
        }
}' --quiet --jsonpprintindent 4

pfurl --verb POST --raw --http 10.17.24.163:5010/api/v1/cmd 
--jsonwrapper 'payload' --msg '
        {   "action": "run",
            "meta":  {
                "cmd":      "$execshell $selfpath/$selfexec --prefix test- --sleepLength 0 /share/incoming /share/outgoing",
                "auid":     "rudolphpienaar",
                "jid":      "simpledsapp-1",
                "threaded": true,
                "container":   {
                        "target": {
                            "image":            "fnndsc/pl-simpledsapp",
                            "cmdParse":         true
                        },
                        "manager": {
                            "image":            "fnndsc/swarm",
                            "app":              "swarm.py",
                            "env":  {
                                "shareDir":     "/home/tmp/share",
                                "serviceType":  "docker",
                                "serviceName":  "testService"
                            }
                        }
                }
            }
        }
'

• Medical data is constrained by many external factors
  
  
   
• Logging and control
• Single shutoff point
  
   
• Communication pathways

• Imaging
  
  
   
• Genomics
• Pathology

• Input DICOM space
• Processed result space
• Structured clinical reporting

• Healthcare compute is at an inflection point
• Lags larger computing -verse
• Many opportunities and challenges exist

• https://github.com/FNNDSC/ChRIS_ultron_backEnd

• https://github.com/FNNDSC/ChRIS_ultron_frontEnd
  

• https://github.com/FNNDSC/viewerjs

• https://github.com/FNNDSC/gcjs

• https://github.com/FNNDSC/fmjs

• https://github.com/FNNDSC/toolbarjs

• https://github.com/FNNDSC/rboxjs

• https://github.com/FNNDSC/rendererjs

• https://github.com/FNNDSC/thbarjs

• https://github.com/FNNDSC/pman

• https://github.com/FNNDSC/pfioh

• https://github.com/FNNDSC/pfcon

• https://goxtk.com
  

• https://github.com/FNNDSC/ami

• Jorge Bernal
• Nicolas Rannou
• Rudolph  Pienaar
• Yangming Ou

• Daniel Haehn
• Daniel Ginsburg

• Ellen Grant

• Orran Krieger
• Ata Turk
• Aditya Awalker

• Dan McPherson
• and others!