Vincent Lequertier
Datos Biográficos
| ID | 5541916 |
|---|---|
| NOMBRE | Vincent Lequertier |
| NOMBRES | Vincent |
| APELLIDO | Lequertier |
| FIRMA | LEQUERTIER V |
| AFILIACIONES | Research on Healthcare Performance (RESHAPE), Université Claude Bernard Lyon 1, INSERM U1290 |
| ORCID | 0000-0001-7904-1961 |
| VERIFICADO | No |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2021 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2024 |
| ÍNDICE H | 0 |
Length of Stay Prediction With Standardized Hospital Data From Acute and Emergency Care Using a Deep Neural Network
OBJECTIVE: Length of stay (LOS) is an important metric for the organization and scheduling of care activities. This study sought to propose a LOS prediction method based on deep learning using widely available administrative data from acute and emergency care and compare it with other methods. PATIENTS AND METHODS: All admissions between January 1, 2011 and December 31, 2019, at 6 university hospitals of the Hospices Civils de Lyon metropolis wer…
Hospital Length of Stay Prediction Methods
OBJECTIVE: This systematic review sought to establish a picture of length of stay (LOS) prediction methods based on available hospital data and study protocols designed to measure their performance. MATERIALS AND METHODS: An English literature search was done relative to hospital LOS prediction from 1972 to September 2019 according to the PRISMA guidelines. Articles were retrieved from PubMed, ScienceDirect, and arXiv databases. Information were …
Sin obras prominentes en esta página.
Hospital Length of Stay Prediction Methods
OBJECTIVE: This systematic review sought to establish a picture of length of stay (LOS) prediction methods based on available hospital data and study protocols designed to measure their performance. MATERIALS AND METHODS: An English literature search was done relative to hospital LOS prediction from 1972 to September 2019 according to the PRISMA guidelines. Articles were retrieved from PubMed, ScienceDirect, and arXiv databases. Information were …
Length of Stay Prediction With Standardized Hospital Data From Acute and Emergency Care Using a Deep Neural Network
OBJECTIVE: Length of stay (LOS) is an important metric for the organization and scheduling of care activities. This study sought to propose a LOS prediction method based on deep learning using widely available administrative data from acute and emergency care and compare it with other methods. PATIENTS AND METHODS: All admissions between January 1, 2011 and December 31, 2019, at 6 university hospitals of the Hospices Civils de Lyon metropolis wer…
Computer Science (2 obras) · Machine learning (2 obras) · Mathematics (2 obras) · Medicine (2 obras) · Sepsis Diagnosis and Treatment (2 obras) · Statistics (2 obras) · Artificial Intelligence (1 obras) · Artificial Intelligence (1 obras) · Cohort (1 obras) · Data mining (1 obras)