Disease distribution modelling
Abstract
In this paper disease distrubution was modelling by randomize method. Cancer distribution in human population was modelling by polynomal distribution probability model. By the derived model virtual experiments of cancer tissue investigation were simulated. The method consists from data collecting about experimental diagnostics, experimental design establishing, selection of mathematical description, parameters estimation, and model adequate examination. How do you seek out sampling function is one of the basic task of modelling this medical system. It is very important how are estimation distribution parameters performed and how defined operation variables according to selected object function. As results of the repeted measurements for the most real experiments different values of measured quantities are obtained.
Keywords:
Diagnostic / population / probability / distribution / cancer / sample takingSource:
Proceedings of the 2nd Wseas International Conference on Biomedical Electronics and Biomedical Infor, 2009, 82-+Publisher:
- World Scientific And Engineering Acad And Soc, Athens
Funding / projects:
- Fund of Serbia
Institution/Community
Inovacioni centarTY - CONF AU - Lukić, Jelena PY - 2009 UR - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/1523 AB - In this paper disease distrubution was modelling by randomize method. Cancer distribution in human population was modelling by polynomal distribution probability model. By the derived model virtual experiments of cancer tissue investigation were simulated. The method consists from data collecting about experimental diagnostics, experimental design establishing, selection of mathematical description, parameters estimation, and model adequate examination. How do you seek out sampling function is one of the basic task of modelling this medical system. It is very important how are estimation distribution parameters performed and how defined operation variables according to selected object function. As results of the repeted measurements for the most real experiments different values of measured quantities are obtained. PB - World Scientific And Engineering Acad And Soc, Athens C3 - Proceedings of the 2nd Wseas International Conference on Biomedical Electronics and Biomedical Infor T1 - Disease distribution modelling EP - + SP - 82 UR - conv_3294 ER -
@conference{ author = "Lukić, Jelena", year = "2009", abstract = "In this paper disease distrubution was modelling by randomize method. Cancer distribution in human population was modelling by polynomal distribution probability model. By the derived model virtual experiments of cancer tissue investigation were simulated. The method consists from data collecting about experimental diagnostics, experimental design establishing, selection of mathematical description, parameters estimation, and model adequate examination. How do you seek out sampling function is one of the basic task of modelling this medical system. It is very important how are estimation distribution parameters performed and how defined operation variables according to selected object function. As results of the repeted measurements for the most real experiments different values of measured quantities are obtained.", publisher = "World Scientific And Engineering Acad And Soc, Athens", journal = "Proceedings of the 2nd Wseas International Conference on Biomedical Electronics and Biomedical Infor", title = "Disease distribution modelling", pages = "+-82", url = "conv_3294" }
Lukić, J.. (2009). Disease distribution modelling. in Proceedings of the 2nd Wseas International Conference on Biomedical Electronics and Biomedical Infor World Scientific And Engineering Acad And Soc, Athens., 82-+. conv_3294
Lukić J. Disease distribution modelling. in Proceedings of the 2nd Wseas International Conference on Biomedical Electronics and Biomedical Infor. 2009;:82-+. conv_3294 .
Lukić, Jelena, "Disease distribution modelling" in Proceedings of the 2nd Wseas International Conference on Biomedical Electronics and Biomedical Infor (2009):82-+, conv_3294 .