G. Tradigo, P. Veltri, O. Marasco, Giovanna Scozzafava, G. Parlato, S. Greco
{"title":"利用GIS研究新生儿TSH分布","authors":"G. Tradigo, P. Veltri, O. Marasco, Giovanna Scozzafava, G. Parlato, S. Greco","doi":"10.1145/2452516.2452523","DOIUrl":null,"url":null,"abstract":"Geographical Information Systems, i.e. GIS, are used to help communities in managing data related to their geographical location. Associating textual data with spatial extension and time can be crucial to understand and improve human health. Exploiting available data and extracting new knowledge can lead to disease distribution and migration models (e.g., epidemiology).\n In this paper we report the experience of using GIS technologies to analyze clinical data containing TSH values about newborn in a spatially delimited region. TSH neonatal screening has been performed on blood of newborn with the aim to discover diseases at an early stage and to study the detect any possible arise of hypothyroidism. We present a flexible geographical system called Geomedica which is being used to analyze such data according to a two steps approach: (i) study of the last 10 years of data distribution in an Italian region with over 18 thousands newborn per year and (ii) identify possible clusters by querying and projecting results geometry on a thematic map.\n Queries performed on the available dataset were able to correctly correlate health data about patients with geographical features (e.g. points of interest, boundaries, coastline vectors) and to visualize diseases distributions on a geographical map. However, the proposed queries may be considered as an important starting point for similar environment dependent pathologies.","PeriodicalId":168309,"journal":{"name":"HealthGIS '12","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Studying neonatal TSH distribution by using GIS\",\"authors\":\"G. Tradigo, P. Veltri, O. Marasco, Giovanna Scozzafava, G. Parlato, S. Greco\",\"doi\":\"10.1145/2452516.2452523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Geographical Information Systems, i.e. GIS, are used to help communities in managing data related to their geographical location. Associating textual data with spatial extension and time can be crucial to understand and improve human health. Exploiting available data and extracting new knowledge can lead to disease distribution and migration models (e.g., epidemiology).\\n In this paper we report the experience of using GIS technologies to analyze clinical data containing TSH values about newborn in a spatially delimited region. TSH neonatal screening has been performed on blood of newborn with the aim to discover diseases at an early stage and to study the detect any possible arise of hypothyroidism. We present a flexible geographical system called Geomedica which is being used to analyze such data according to a two steps approach: (i) study of the last 10 years of data distribution in an Italian region with over 18 thousands newborn per year and (ii) identify possible clusters by querying and projecting results geometry on a thematic map.\\n Queries performed on the available dataset were able to correctly correlate health data about patients with geographical features (e.g. points of interest, boundaries, coastline vectors) and to visualize diseases distributions on a geographical map. However, the proposed queries may be considered as an important starting point for similar environment dependent pathologies.\",\"PeriodicalId\":168309,\"journal\":{\"name\":\"HealthGIS '12\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HealthGIS '12\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2452516.2452523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HealthGIS '12","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2452516.2452523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geographical Information Systems, i.e. GIS, are used to help communities in managing data related to their geographical location. Associating textual data with spatial extension and time can be crucial to understand and improve human health. Exploiting available data and extracting new knowledge can lead to disease distribution and migration models (e.g., epidemiology).
In this paper we report the experience of using GIS technologies to analyze clinical data containing TSH values about newborn in a spatially delimited region. TSH neonatal screening has been performed on blood of newborn with the aim to discover diseases at an early stage and to study the detect any possible arise of hypothyroidism. We present a flexible geographical system called Geomedica which is being used to analyze such data according to a two steps approach: (i) study of the last 10 years of data distribution in an Italian region with over 18 thousands newborn per year and (ii) identify possible clusters by querying and projecting results geometry on a thematic map.
Queries performed on the available dataset were able to correctly correlate health data about patients with geographical features (e.g. points of interest, boundaries, coastline vectors) and to visualize diseases distributions on a geographical map. However, the proposed queries may be considered as an important starting point for similar environment dependent pathologies.