Intelligible Support Vector Machines for Diagnosis of Diabetes Mellitus

By Nahla H. Barakat, Andrew P. Bradley, Mohamed Nabil H. Barakat. IEEE Transactions on Information Technology in Biomedicine, 2010

375 citations recorded by the source corpus.

Subfields: Complementary and alternative medicine, Endocrinology, Diabetes and Metabolism, Health Information Management

View Paper: https://www.semanticscholar.org/paper/5773640ff1eb454fe2f234f4ea0ca286c0790c8b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Complementary and alternative medicine

1. V. Kumari
2. R. Chitra

In Health Information Management

1. V. Kumari
2. R. Chitra

Citations in the corpus

• Classification Of Diabetes Disease Using Support Vector Machine (2013, background): “Diabetes disease diagnosis and interpretation of the diabetes data is an important classification problem [5].”