Publicação
A survival prediction model for colorectal cancer patients
| Resumo: | The importance of making predictions in health is mainly linked to the decision-making process. Make survival predictions accurately is a very difficult task for healthcare professionals and a major concern for patients. On the one hand, it can help physicians decide between palliative care or other medical practice for a patient. On the other hand, the notion of remaining lifetime could help patients in the realization of dreams. However, the prediction of survivability is directly related to the experience of health professionals and their ability to memorize. Most decisions are made based on probability and statistics, but these are based on large groups of people and may not be suitable to predict what will happen in particular cases. Consequently, the use of machine learning techniques have been explored in healthcare. Their ability to help solve diagnostic and prognosis problems has been increasingly exploited. The main contribution of this work is a prediction tool of survival of patients with cancer of the colon and/or rectum, after treatment and a few years after treatment. The characteristics that distinguishes it is the balance between the number of required inputs and their performance in terms of prediction. The tool is compatible with mobile devices, includes a online learning component that allows for automatic recalculation and flexibly of the prediction models, by adding new cases. The tool aims to facilitate the access of healthcare professionals for instruments that enrich their practice and improve their results. This increases the productivity of healthcare professionals, enabling them to make decisions faster and with a lower error rate. |
|---|---|
| Autores principais: | Silva, Ana Paula Pinto da |
| Assunto: | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| Ano: | 2016 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| _version_ | 1867439621352194048 |
|---|---|
| author | Silva, Ana Paula Pinto da |
| author_facet | Silva, Ana Paula Pinto da |
| author_role | author |
| contributor_name_str_mv | Novais, Paulo RepositóriUM - Universidade do Minho |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Silva, Ana Paula Pinto da\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Novais, Paulo RepositóriUM - Universidade do Minho |
| datacite.creators.creator.creatorName.fl_str_mv | Silva, Ana Paula Pinto da |
| datacite.date.Accepted.fl_str_mv | 2016-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2017-10-19T11:27:02Z |
| datacite.date.embargoed.fl_str_mv | 2017-10-19T11:27:02Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| datacite.titles.title.fl_str_mv | A survival prediction model for colorectal cancer patients |
| dc.contributor.none.fl_str_mv | Novais, Paulo RepositóriUM - Universidade do Minho |
| dc.creator.none.fl_str_mv | Silva, Ana Paula Pinto da |
| dc.date.Accepted.fl_str_mv | 2016-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2017-10-19T11:27:02Z |
| dc.date.embargoed.fl_str_mv | 2017-10-19T11:27:02Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://hdl.handle.net/1822/46708 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| dc.title.fl_str_mv | A survival prediction model for colorectal cancer patients |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | The importance of making predictions in health is mainly linked to the decision-making process. Make survival predictions accurately is a very difficult task for healthcare professionals and a major concern for patients. On the one hand, it can help physicians decide between palliative care or other medical practice for a patient. On the other hand, the notion of remaining lifetime could help patients in the realization of dreams. However, the prediction of survivability is directly related to the experience of health professionals and their ability to memorize. Most decisions are made based on probability and statistics, but these are based on large groups of people and may not be suitable to predict what will happen in particular cases. Consequently, the use of machine learning techniques have been explored in healthcare. Their ability to help solve diagnostic and prognosis problems has been increasingly exploited. The main contribution of this work is a prediction tool of survival of patients with cancer of the colon and/or rectum, after treatment and a few years after treatment. The characteristics that distinguishes it is the balance between the number of required inputs and their performance in terms of prediction. The tool is compatible with mobile devices, includes a online learning component that allows for automatic recalculation and flexibly of the prediction models, by adding new cases. The tool aims to facilitate the access of healthcare professionals for instruments that enrich their practice and improve their results. This increases the productivity of healthcare professionals, enabling them to make decisions faster and with a lower error rate. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://repositorium.uminho.pt/bitstreams/effbae01-e437-4d90-ae9a-eb0bda49674b/download |
| id | rum_3cc6e893b2ee33c57a4f0134ddb0e42d |
| identifier.url.fl_str_mv | https://hdl.handle.net/1822/46708 |
| instacron_str | repositorium |
| institution | Universidade do Minho |
| instname_str | Universidade do Minho |
| language | eng |
| network_acronym_str | rum |
| network_name_str | RepositóriUM - Universidade do Minho |
| oai_identifier_str | oai:repositorium.uminho.pt:1822/46708 |
| organization_str_mv | urn:organizationAcronym:repositorium |
| person_str_mv | Silva, Ana Paula Pinto da |
| publishDate | 2016 |
| reponame_str | RepositóriUM - Universidade do Minho |
| repository_id_str | urn:repositoryAcronym:rum |
| service_str_mv | urn:repositoryAcronym:rum |
| spelling | engporThe importance of making predictions in health is mainly linked to the decision-making process. Make survival predictions accurately is a very difficult task for healthcare professionals and a major concern for patients. On the one hand, it can help physicians decide between palliative care or other medical practice for a patient. On the other hand, the notion of remaining lifetime could help patients in the realization of dreams. However, the prediction of survivability is directly related to the experience of health professionals and their ability to memorize. Most decisions are made based on probability and statistics, but these are based on large groups of people and may not be suitable to predict what will happen in particular cases. Consequently, the use of machine learning techniques have been explored in healthcare. Their ability to help solve diagnostic and prognosis problems has been increasingly exploited. The main contribution of this work is a prediction tool of survival of patients with cancer of the colon and/or rectum, after treatment and a few years after treatment. The characteristics that distinguishes it is the balance between the number of required inputs and their performance in terms of prediction. The tool is compatible with mobile devices, includes a online learning component that allows for automatic recalculation and flexibly of the prediction models, by adding new cases. The tool aims to facilitate the access of healthcare professionals for instruments that enrich their practice and improve their results. This increases the productivity of healthcare professionals, enabling them to make decisions faster and with a lower error rate.application/pdfporA survival prediction model for colorectal cancer patientsSilva, Ana Paula Pinto daNovais, PauloHostingInstitutionOrganizationalRepositóriUM - Universidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptTID2015536272017-10-19T11:27:02Z201620162016-01-01T00:00:00ZHandlehttps://hdl.handle.net/1822/46708http://purl.org/coar/access_right/c_abf2open accesshttp://www.oecd.org/science/inno/38235147.pdfFields of Science and Technology (FOS)Engenharia e Tecnologia::Outras Engenharias e Tecnologias8204470 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorium.uminho.pt/bitstreams/effbae01-e437-4d90-ae9a-eb0bda49674b/download |
| spellingShingle | A survival prediction model for colorectal cancer patients Silva, Ana Paula Pinto da Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| status | SINGLETON |
| subject.other.fl_str_mv | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| title | A survival prediction model for colorectal cancer patients |
| title_full | A survival prediction model for colorectal cancer patients |
| title_fullStr | A survival prediction model for colorectal cancer patients |
| title_full_unstemmed | A survival prediction model for colorectal cancer patients |
| title_short | A survival prediction model for colorectal cancer patients |
| title_sort | A survival prediction model for colorectal cancer patients |
| topic | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| topic_facet | Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| url | https://hdl.handle.net/1822/46708 |
| visible | 1 |