A Pre-Diagnosis Model for Indoor Radon Potential Assessment

Bibliographic Details
Main Author: Meneses, Paulo
Publication Date: 2023
Other Authors: Lopes, Nuno, Leite, Patrícia, Texeira, Paulo, Gonçalves, Joaquim, Silva, joaquim P
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/11110/3206
Summary: Indoor radon is a well-known public health threat. WHO estimates radon causes between 3-14% of all lung cancers and has issued many recommendations to encourage countries to act against the exposure to radon and associated cancer risks. However, many people continue to be unaware about radon health risk. In previous works we developed a prediagnosis approach to evaluate the radon potential in indoor environments and motivate the citizens to act when the estimated radon potential is higher. In this work, we have developed an automatic classification model for the evaluation of the radon potential level in indoor environments by considering a set of relevant features selected to characterize occupants' risk exposure. Radon data measurements from previous works have been merged and provide enough data for the start of this project. The evaluation metrics of the obtained classification model are compelling and represent a good starting point for the development of a platform that will help to raise awareness of the radon risk and promote radon measurements to the wider population. These measurements will be used as new data for the generation of more robust classification models.
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spelling A Pre-Diagnosis Model for Indoor Radon Potential AssessmentIndoor Radon Assessment,Indoor RadonIndoor Radon Potential ClassificationRadon Performance IndicatorIndoor radon is a well-known public health threat. WHO estimates radon causes between 3-14% of all lung cancers and has issued many recommendations to encourage countries to act against the exposure to radon and associated cancer risks. However, many people continue to be unaware about radon health risk. In previous works we developed a prediagnosis approach to evaluate the radon potential in indoor environments and motivate the citizens to act when the estimated radon potential is higher. In this work, we have developed an automatic classification model for the evaluation of the radon potential level in indoor environments by considering a set of relevant features selected to characterize occupants' risk exposure. Radon data measurements from previous works have been merged and provide enough data for the start of this project. The evaluation metrics of the obtained classification model are compelling and represent a good starting point for the development of a platform that will help to raise awareness of the radon risk and promote radon measurements to the wider population. These measurements will be used as new data for the generation of more robust classification models.This research was funded by the project TECH - Technology, Environment, Creativity and Health, Norte-01-0145-FEDER-000043, supported by Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF)2023-01-01T00:00:00Z2025-03-17info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/11110/3206http://hdl.handle.net/11110/3206engmetadata only accessinfo:eu-repo/semantics/openAccessMeneses, PauloLopes, NunoLeite, PatríciaTexeira, PauloGonçalves, JoaquimSilva, joaquim Preponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-20T06:31:45Zoai:ciencipca.ipca.pt:11110/3206Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T04:38:13.409977Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A Pre-Diagnosis Model for Indoor Radon Potential Assessment
title A Pre-Diagnosis Model for Indoor Radon Potential Assessment
spellingShingle A Pre-Diagnosis Model for Indoor Radon Potential Assessment
Meneses, Paulo
Indoor Radon Assessment,
Indoor Radon
Indoor Radon Potential Classification
Radon Performance Indicator
title_short A Pre-Diagnosis Model for Indoor Radon Potential Assessment
title_full A Pre-Diagnosis Model for Indoor Radon Potential Assessment
title_fullStr A Pre-Diagnosis Model for Indoor Radon Potential Assessment
title_full_unstemmed A Pre-Diagnosis Model for Indoor Radon Potential Assessment
title_sort A Pre-Diagnosis Model for Indoor Radon Potential Assessment
author Meneses, Paulo
author_facet Meneses, Paulo
Lopes, Nuno
Leite, Patrícia
Texeira, Paulo
Gonçalves, Joaquim
Silva, joaquim P
author_role author
author2 Lopes, Nuno
Leite, Patrícia
Texeira, Paulo
Gonçalves, Joaquim
Silva, joaquim P
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Meneses, Paulo
Lopes, Nuno
Leite, Patrícia
Texeira, Paulo
Gonçalves, Joaquim
Silva, joaquim P
dc.subject.por.fl_str_mv Indoor Radon Assessment,
Indoor Radon
Indoor Radon Potential Classification
Radon Performance Indicator
topic Indoor Radon Assessment,
Indoor Radon
Indoor Radon Potential Classification
Radon Performance Indicator
description Indoor radon is a well-known public health threat. WHO estimates radon causes between 3-14% of all lung cancers and has issued many recommendations to encourage countries to act against the exposure to radon and associated cancer risks. However, many people continue to be unaware about radon health risk. In previous works we developed a prediagnosis approach to evaluate the radon potential in indoor environments and motivate the citizens to act when the estimated radon potential is higher. In this work, we have developed an automatic classification model for the evaluation of the radon potential level in indoor environments by considering a set of relevant features selected to characterize occupants' risk exposure. Radon data measurements from previous works have been merged and provide enough data for the start of this project. The evaluation metrics of the obtained classification model are compelling and represent a good starting point for the development of a platform that will help to raise awareness of the radon risk and promote radon measurements to the wider population. These measurements will be used as new data for the generation of more robust classification models.
publishDate 2023
dc.date.none.fl_str_mv 2023-01-01T00:00:00Z
2025-03-17
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