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Y. Sucharitha

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Conference Aug 2026

An Explainable Transfer Learning Framework for Breast Cancer Classification Using Deep CNN Models

When it comes to cancers affecting women, breast cancer is still at the top of the list and a huge problem for public health. The key to better patient outcomes and lower mortality rates is early and precise diagnosis. In order to overcome these obstacles, this research presents a hybrid framework that uses deep learni...

D. Baswaraj, Y. Sucharitha, S. Nithyapriya et al. · 0 citations
Conference Aug 2026

A Multi-Model Fusion Deep Learning Framework for Blood Glucose Prediction from Historical Glucose Signals

Regular monitoring of blood glucose levels is essential for those with diabetes mellitus, a chronic condition. Neglecting to maintain a steady blood glucose level may have serious effects for the person. This is why blood glucose (BG) prediction has been the subject of a great deal of research. In order to make an accu...

Priya Shirley Muller, N. S. R. Rama Raju, S. Yuvalatha et al. · 0 citations
Review Sep 2026

Explainable AI in MRI-Based Brain Tumor Segmentation: Advances, Challenges, Opportunities, and Future Directions

Untreated brain tumors (BT) cause abnormal growth of brain tissue and pose serious health risks, including the possibility of death. Because of its high resolution and ability to differentiate between different types of tissues, magnetic-resonance-imaging (MRI) has replaced previous imaging modalities as the gold s...

K. Arunkumar, U. Veeresh, Y. Sucharitha et al. · 0 citations

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