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X Demographics
Mendeley readers
Title |
Deep hybrid model for maternal health risk classification in pregnancy: synergy of ANN and random forest
|
---|---|
Published in |
Frontiers in Artificial Intelligence, July 2023
|
DOI | 10.3389/frai.2023.1213436 |
Pubmed ID | |
Authors |
Taofeeq Oluwatosin Togunwa, Abdulhammed Opeyemi Babatunde, Khalil-ur-Rahman Abdullah |
X Demographics
The data shown below were collected from the profiles of 71 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Nigeria | 25 | 35% |
Switzerland | 2 | 3% |
Austria | 1 | 1% |
Comoros | 1 | 1% |
United States | 1 | 1% |
Mexico | 1 | 1% |
Ghana | 1 | 1% |
Unknown | 39 | 55% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 50 | 70% |
Practitioners (doctors, other healthcare professionals) | 19 | 27% |
Scientists | 2 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 5 | 14% |
Unspecified | 3 | 8% |
Lecturer | 3 | 8% |
Other | 1 | 3% |
Researcher | 1 | 3% |
Other | 3 | 8% |
Unknown | 21 | 57% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 8 | 22% |
Unspecified | 3 | 8% |
Medicine and Dentistry | 3 | 8% |
Mathematics | 1 | 3% |
Design | 1 | 3% |
Other | 0 | 0% |
Unknown | 21 | 57% |