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020 _a9783662562918
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082 0 4 _a006.3
_223
100 1 _aParanjape, Raman.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 4 _aThe Diabetic Patient Agent
_h[electronic resource] :
_bModeling Disease in Humans and the Healthcare System Response /
_cby Raman Paranjape, Zhanle (Gerald) Wang, Simerjit Gill.
250 _a1st ed. 2018.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2018.
300 _aXIV, 123 p. 81 illus., 74 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v133
500 _aAcceso multiusuario
505 0 _aIntroduction.- Agent-based Modeling and Simulation.- The Ackerman Mathematical Model.- Patient-physician interaction model.- Simulation Results.- Control patient Agent Model -- Self Aware patient Agent Model -- Blood Glucose Monitoring Frequency Evaluation.- Conclusions and future work.
520 _aThis book provides a pioneering approach to modeling the human diabetic patient using a software agent. It is based on two MASc (Master of Applied Science) theses: one looking at the evolution of the patient agent in time, and another looking the interaction of the patient agent with the healthcare system. It shows that the software agent evolves in a manner analogous to the human patient and exhibits typical attributes of the illness such as reacting to food consumption, medications, and activity. This agent model can be used in a number of different ways, including as a prototype for a specific human patient with the purpose of helping to identify when that patient's condition deviates from normal variations. The software agent can also be used to study the interaction between the human patient and the health care system. This book is of interest to anyone involved in the management of diabetic patients or in societal research into the management of diabetes. The diabetic patient agent was developed using the Ackerman model for diabetes, but this model can be easily adapted for any other model subject with the necessary physiological data to support that model.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aComputational intelligence.
650 0 _aDiabetes.
650 0 _aBiomedical engineering.
650 0 _aArtificial intelligence.
650 0 _aHealth informatics.
650 0 _aHealth administration.
650 1 4 _aComputational Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T11014
650 2 4 _aDiabetes.
_0https://scigraph.springernature.com/ontologies/product-market-codes/H33045
650 2 4 _aBiomedical Engineering and Bioengineering.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T2700X
650 2 4 _aArtificial Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
650 2 4 _aHealth Informatics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/H28009
650 2 4 _aHealth Administration.
_0https://scigraph.springernature.com/ontologies/product-market-codes/H27030
700 1 _aWang, Zhanle (Gerald).
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aGill, Simerjit.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783662562895
776 0 8 _iPrinted edition:
_z9783662562901
776 0 8 _iPrinted edition:
_z9783662572597
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v133
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-662-56291-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c243149
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