Name
Title | ||
|---|---|---|
Predicting life expectancy with a long short-term memory recurrent neural network using electronic medical records. |
Abstract | ||
|---|---|---|
Prognostication of life expectancy is difficult for humans. Our research shows that machine learning and natural language processing techniques offer a feasible and promising approach to predicting life expectancy. The research has potential for real-life applications, such as supporting timely recognition of the right moment to start Advance Care Planning. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1186/s12911-019-0775-2 | BMC medical informatics and decision making |
Keywords | Field | DocType |
Advance care planning,Clinical free-text,Life expectancy prediction,Long short-term memory | Health care,Window of opportunity,Advance care planning,Recurrent neural network,Knowledge management,Life expectancy,Medical record,Medical emergency,Procurement,Health informatics,Medicine | Journal |
Volume | Issue | ISSN |
19 | 1 | 1472-6947 |
Citations | PageRank | References |
2 | 0.44 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Merijn Beeksma | 1 | 2 | 0.44 |
| Suzan Verberne | 2 | 233 | 32.09 |
| Antal Van Den Bosch | 3 | 1038 | 132.37 |
| enny das | 4 | 4 | 1.15 |
| Iris Hendrickx | 5 | 285 | 30.91 |
| Stef Groenewoud | 6 | 2 | 0.44 |