You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Chapter title |
Early Prediction of Severe Maternal Morbidity Using Machine Learning Techniques
|
---|---|
Chapter number | 22 |
Book title |
Advances in Artificial Intelligence - IBERAMIA 2016
|
Published by |
Springer International Publishing, January 2016
|
DOI | 10.1007/978-3-319-47955-2_22 |
Book ISBNs |
978-3-31-947954-5, 978-3-31-947955-2
|
Authors |
Eugenia Arrieta Rodríguez, Francisco Edna Estrada, William Caicedo Torres, Juan Carlos Martínez Santos |
Editors |
Manuel Montes y Gómez, Hugo Jair Escalante, Alberto Segura, Juan de Dios Murillo |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 3% |
Unknown | 35 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 7 | 19% |
Student > Bachelor | 5 | 14% |
Student > Master | 5 | 14% |
Lecturer | 2 | 6% |
Professor | 2 | 6% |
Other | 4 | 11% |
Unknown | 11 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 28% |
Medicine and Dentistry | 5 | 14% |
Nursing and Health Professions | 3 | 8% |
Engineering | 2 | 6% |
Unspecified | 1 | 3% |
Other | 2 | 6% |
Unknown | 13 | 36% |