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Mendeley readers
Chapter title |
Comparing Machine Learning Algorithms to Predict Diabetes in Women and Visualize Factors Affecting It the Most—A Step Toward Better Health Care for Women
|
---|---|
Chapter number | 29 |
Book title |
International Conference on Innovative Computing and Communications
|
Published by |
Springer, Singapore, February 2020
|
DOI | 10.1007/978-981-15-1286-5_29 |
Book ISBNs |
978-9-81-151285-8, 978-9-81-151286-5
|
Authors |
Arushi Agarwal, Ankur Saxena, Agarwal, Arushi, Saxena, Ankur |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 12 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Doctoral Student | 3 | 25% |
Student > Bachelor | 2 | 17% |
Lecturer | 1 | 8% |
Student > Ph. D. Student | 1 | 8% |
Student > Postgraduate | 1 | 8% |
Other | 0 | 0% |
Unknown | 4 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 5 | 42% |
Biochemistry, Genetics and Molecular Biology | 1 | 8% |
Economics, Econometrics and Finance | 1 | 8% |
Engineering | 1 | 8% |
Unknown | 4 | 33% |