Agent-Based modeling in Medical Research. Example in Health Economics
This chapter presents the main lines of agent based modeling in the field of medical research. The general diagram consists of a cohort of patients (virtual or real) whose evolution is observed by means of so-called evolution models. Scenarios can then be explored by varying the parameters of the di...
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| creator | Saint-Pierre, Philippe Demeulemeester, Romain Costa, Nadège Savy, Nicolas |
| description | This chapter presents the main lines of agent based modeling in the field of
medical research. The general diagram consists of a cohort of patients (virtual
or real) whose evolution is observed by means of so-called evolution models.
Scenarios can then be explored by varying the parameters of the different
models. This chapter presents techniques for virtual patient generation and
examples of execution models. The advantages and disadvantages of these models
are discussed as well as the pitfalls to be avoided. Finally, an application to
the medico-economic study of the impact of the penetration rate of generic
versions of treatments on the costs associated with HIV treatment is presented. |
| doi_str_mv | 10.48550/arxiv.2205.10131 |
| format | Article |
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medical research. The general diagram consists of a cohort of patients (virtual
or real) whose evolution is observed by means of so-called evolution models.
Scenarios can then be explored by varying the parameters of the different
models. This chapter presents techniques for virtual patient generation and
examples of execution models. The advantages and disadvantages of these models
are discussed as well as the pitfalls to be avoided. Finally, an application to
the medico-economic study of the impact of the penetration rate of generic
versions of treatments on the costs associated with HIV treatment is presented.</description><identifier>DOI: 10.48550/arxiv.2205.10131</identifier><language>eng</language><subject>Computer Science - Artificial Intelligence ; Statistics - Methodology</subject><creationdate>2022-05</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2205.10131$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2205.10131$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Saint-Pierre, Philippe</creatorcontrib><creatorcontrib>Demeulemeester, Romain</creatorcontrib><creatorcontrib>Costa, Nadège</creatorcontrib><creatorcontrib>Savy, Nicolas</creatorcontrib><title>Agent-Based modeling in Medical Research. Example in Health Economics</title><description>This chapter presents the main lines of agent based modeling in the field of
medical research. The general diagram consists of a cohort of patients (virtual
or real) whose evolution is observed by means of so-called evolution models.
Scenarios can then be explored by varying the parameters of the different
models. This chapter presents techniques for virtual patient generation and
examples of execution models. The advantages and disadvantages of these models
are discussed as well as the pitfalls to be avoided. Finally, an application to
the medico-economic study of the impact of the penetration rate of generic
versions of treatments on the costs associated with HIV treatment is presented.</description><subject>Computer Science - Artificial Intelligence</subject><subject>Statistics - Methodology</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz8FuwjAQBFBfeqgoH9BT_QMJ9jp2nCOgFCpRVaq4R2t7A5acBCWogr-n0J7mMJqRHmOvUuSF1VoscLzEnxxA6FwKqeQzq5cH6s_ZCicKvBsCpdgfeOz5J4XoMfFvmghHf8x5fcHulOhebgnT-chrP_RDF_30wp5aTBPN_3PG9u_1fr3Ndl-bj_Vyl6EpZeZAhdZIaxGNEU7ZQK0qDIFTrlDCAvrKGg2mBAJRVkDCygp-t7qoSmfVjL393T4czWmMHY7X5u5pHh51A7X5Q1s</recordid><startdate>20220518</startdate><enddate>20220518</enddate><creator>Saint-Pierre, Philippe</creator><creator>Demeulemeester, Romain</creator><creator>Costa, Nadège</creator><creator>Savy, Nicolas</creator><scope>AKY</scope><scope>EPD</scope><scope>GOX</scope></search><sort><creationdate>20220518</creationdate><title>Agent-Based modeling in Medical Research. Example in Health Economics</title><author>Saint-Pierre, Philippe ; Demeulemeester, Romain ; Costa, Nadège ; Savy, Nicolas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a671-b23df6188aa660b38def346e2b3b43082ac98652672e20792e08192a675497b83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Computer Science - Artificial Intelligence</topic><topic>Statistics - Methodology</topic><toplevel>online_resources</toplevel><creatorcontrib>Saint-Pierre, Philippe</creatorcontrib><creatorcontrib>Demeulemeester, Romain</creatorcontrib><creatorcontrib>Costa, Nadège</creatorcontrib><creatorcontrib>Savy, Nicolas</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv Statistics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Saint-Pierre, Philippe</au><au>Demeulemeester, Romain</au><au>Costa, Nadège</au><au>Savy, Nicolas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Agent-Based modeling in Medical Research. Example in Health Economics</atitle><date>2022-05-18</date><risdate>2022</risdate><abstract>This chapter presents the main lines of agent based modeling in the field of
medical research. The general diagram consists of a cohort of patients (virtual
or real) whose evolution is observed by means of so-called evolution models.
Scenarios can then be explored by varying the parameters of the different
models. This chapter presents techniques for virtual patient generation and
examples of execution models. The advantages and disadvantages of these models
are discussed as well as the pitfalls to be avoided. Finally, an application to
the medico-economic study of the impact of the penetration rate of generic
versions of treatments on the costs associated with HIV treatment is presented.</abstract><doi>10.48550/arxiv.2205.10131</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Artificial Intelligence Statistics - Methodology |
| title | Agent-Based modeling in Medical Research. Example in Health Economics |
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