Difference between revisions of "File:Fig1 Pathinarupothi BMCMedInfoDecMak2018 18.png"

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Description	Figure 1. RASPRO-PAF framework. The architecture shows the RASPRO-PAF framework, which progressively converts the raw multi-sensor data into quantized symbols, helpful motifs, diagnostic predictions, and critical alerts.
Source	Pathinarupothi, R.K.; Durga, P.; Rangan, E.S. (2018). "Data to diagnosis in global health: A 3P approach". BMC Medical Informatics and Decision Making 18: 78. doi:10.1186/s12911-018-0658-y.
Date	2018
Author	Pathinarupothi, R.K.; Durga, P.; Rangan, E.S.
Permission (Reusing this file)	Creative Commons Attribution 4.0 International
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 ==Summary==
 {{Information
-|Description='''Figure 1.''' RASPRO-PAF framework. The architecture shows the RASPRO-PAF framework, which progressively converts the raw multi-sensor data into quantized symbols, helpful motifs, diagnostic predictions, and critical alerts. |title=Data to diagnosis in global health: A 3P approach |journal=BMC Medical Informatics and Decision Making |author=Pathinarupothi, R.K.; Durga, P.; Rangan, E.S. |volume=18 |pages=78 |year=2018 |doi=10.1186/s12911-018-0658-y}}
+|Description='''Figure 1.''' RASPRO-PAF framework. The architecture shows the RASPRO-PAF framework, which progressively converts the raw multi-sensor data into quantized symbols, helpful motifs, diagnostic predictions, and critical alerts. |Source={{cite journal |title=Data to diagnosis in global health: A 3P approach |journal=BMC Medical Informatics and Decision Making |author=Pathinarupothi, R.K.; Durga, P.; Rangan, E.S. |volume=18 |pages=78 |year=2018 |doi=10.1186/s12911-018-0658-y}}
 |Author=Pathinarupothi, R.K.; Durga, P.; Rangan, E.S.
 |Date=2018