CHITRAL: Researchers from the University of Chitral have published a study detailing a novel approach to diabetes prediction using machine learning techniques. The research, led by Mr. Toufeeq Ur Rehman and Junaid Iqbal, a student in the Department of Computer Science, was conducted under the supervision of Mr. Malak Roman, a lecturer in the same department.

The article, titled “A Comparative Machine Learning Approach to Diabetes Prediction: Integrating Best First Search Feature Selection with SVM and Naïve Bayes Classifiers,” has been published in the peer-reviewed journal Spectrum of Engineering Sciences, which is recognized by the Higher Education Commission (HEC).

The study examines the effectiveness of combining Best First Search feature selection with Support Vector Machine (SVM) and Naïve Bayes classifiers to enhance the accuracy of diabetes predictions. The findings provide insights into potential improvements in predictive modeling for healthcare applications.

The full article is accessible through the journal’s publication platform, allowing other researchers to review and build upon the work conducted by the University of Chitral team.