Sk Hasane Ahammad

Abstract Classification of brain tumors is a difficult problem in medical imaging analysis. Over the past few years, various deep learning-based techniques have been employed for detecting and classifying tumors from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). In this paper, a new model referred to as Multimodal Attention based Convolutional Neural Network (MANet) has been proposed for detection and classification of brain tumors.

C. V.Anupama, D.Devarapalli, S. H.Ahammad, and A. N. Z.Rashed, “Deep Cervical Cancer Prediction Network With Few Shots Learning for Cervical Cancer Prediction and Classification,” Transactions on Emerging Telecommunications Technologies37, no. 5 (2026): e70431, https://doi.org/10.1002/ett.70431. Conflicts of Interest The authors declare no conflicts of interest.

Abstract Globally, breast cancer is one the life-threatening diseases among women. Breast histopathological image (HI) investigation is the most effective method applied for the recognition of cancer malignancy. Manual breast HI investigation is, still, time-consuming, abstract, and susceptible to human errors. Computer-aided diagnosis (CAD) became a possible and popular solution for medicinal image investigation owing to current developments in computer memory and power.