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Ms. Kanimozhi Janarthanan
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Academic Career Length
2Years (2025-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
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Conference Paper
SRSANMUGASUNDARAM RAVICHANDRAN
SANMUGASUNDARAM RAVICHANDRANHSHui-Kai Su
Hui-Kai SuWKWen-Kai Kuo
Wen-Kai KuoMMManikandan Mahalingam
Manikandan MahalingamKJKanimozhi Janarthanan
Kanimozhi JanarthananBSBruhathi Sathyanarayanan
Bruhathi Sathyanarayanan +1
Advancements in image processing have advanced medical diagnostics, especially in image classification, impacting healthcare by offering faster and more accurate analyses of magnetic resonance imaging (MRI) and X-rays. The manual examination of these images is slow, error-prone, and costly. Therefore, we propose a new method focusing on the Pap smear exam for early cervical cancer detection. Using a convolutional neural network (CNN) and the SIPaKMeD dataset, cervical cells are classified into normal, precancerous, and benign cells after segmentation. The CNN’s architecture is simple yet efficient, achieving a 91.29% accuracy.
Conference Paper
SRSANMUGASUNDARAM RAVICHANDRAN
SANMUGASUNDARAM RAVICHANDRANHSHui-Kai Su
Hui-Kai SuWKWen-Kai Kuo
Wen-Kai KuoMMManikandan Mahalingam
Manikandan MahalingamKJKanimozhi Janarthanan
Kanimozhi JanarthananKSKabilan S
Kabilan S +1
We implemented a robust framework for diabetes prediction, leveraging a diverse array of machine learning algorithms. Through an analysis of diabetes-related characteristics, we identified the most accurate classifier. Diverse algorithms were tested to compare their accuracies with the complexities of data: K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), logistic regression (LR), Naïve Bayes (NB), and decision tree (DT). The decision tree algorithm demonstrated the best accuracy in predicting diabetes.
About Me
Kanimozhi Janarthanan was born in 2003 in Arakkonam, Tamil Nadu, India. She is currently pursuing her Bachelor of Engineering degree in Computer and Communication Engineering at Rajalakshmi Institute of Technology, with graduation expected in 2025.
With a keen interest in cutting-edge technologies, Kanimozhi has developed a strong foundation in machine learning and data science, actively engaging in projects and coursework that reflect her passion for intelligent systems and data-driven solutions. Throughout her academic journey, she has demonstrated dedication and curiosity, continuously seeking opportunities to expand her knowledge and practical skills in the field.