| DC Field | Value | Language |
|---|
| dc.contributor.advisor | Konzen, Andrea Aparecida | - |
| dc.contributor.author | Magistral, Larissa dos Santos | - |
| dc.contributor.author | Santos, Nikolas Lacerda | - |
| dc.date.accessioned | 2024-07-01T11:56:50Z | - |
| dc.date.available | 2024-07-01T11:56:50Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.uri | https://hdl.handle.net/10923/26145 | - |
| dc.description.abstract | The length of hospital stays of patients is a fun damental factor for the planning and effective management of hospital resources. With the advancement of machine learning and the increasing availability of data in healthcare, there is an opportunity and an important interest in predicting the length of hospital stays of patients in order to improve the quality of patient care, decrease costs operations, increase service efficiency and help with discharge planning. In this work, a proposal for a customized model will be presented to determine the length of hospital stays. | en |
| dc.language.iso | pt_BR | pt_BR |
| dc.rights | openAccess | - |
| dc.title | Previsão de tempo de uso de leitos hospitalares com Aprendizado de Máquina | pt_BR |
| dc.type | Article | pt_BR |
| dc.degree.grantor | Pontifícia Universidade Católica do Rio Grande do Sul | - |
| dc.degree.department | Escola Politécnica | - |
| dc.degree.local | Porto Alegre | - |
| dc.degree.level | Graduação | - |
| dc.degree.date | 2022/2 | - |
| dc.degree.graduation | Ciência da Computação | - |
| Appears in Collections: | TCC Ciência da Computação
|
