| Accession |
PRJCA018425 |
| Title |
Research on Intelligent Localization of Newborn Tracheal intubation Chest Film Based on Artificial Intelligence (AI) |
| Relevance |
Medical |
| Data types |
chest X ray
|
| Organisms |
Homo sapiens
|
| Description |
At the invitation of Professor Pranav Rajpurkar's research team at Harvard Medical School in the United States, we want to join the construction of a public multi-institution imaging dataset called Artificial Intelligence Data for All Healthcare (MAIDA). By sharing the chest film and basic patient information of 50 children with tracheal intubation in the neonatal intensive care unit of our hospital with de-identification, an automatic evaluation model for tracheal intubation placement was developed based on artificial intelligence (AI) algorithm to realize the immediate evaluation of tracheal intubation positioning of newborns, reducing the burden on radiologists and front-line clinicians. It also provides better outcomes for evaluating patients in the neonatal intensive care unit. Of course, working with multidisciplinary teams abroad to manage AI-based datasets with relevant clinical information and high-quality annotations increases the diversity of regional and hospital sources for research. |
| Sample scope |
Multiisolate |
| Release date |
2023-07-17 |
| Grants |
| Agency |
program |
Grant ID |
Grant title |
| No funding support
|
|
|
|
|
|
| Submitter |
Binzhi
Tang (tomabishi@163.com)
|
| Organization |
Sichuan Provincial People's Hospital |
| Submission date |
2023-07-17 |
