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IEEE/ACM Transactions on Computational Biology and Bioinformatics|August 22, 2022
Proposal of SVM Utility Kernel for Breast Cancer Survival EstimationNikhilanand Arya, Archana Mathur, Snehanshu Saha, et al.
Scientific Reports|March 11, 2023
Improving the robustness and stability of a machine learning model for breast cancer prognosis through the use of multi-modal classifiersNikhilanand Arya, Sriparna Saha, Archana Mathur, et al.
Chaos (Woodbury, N.Y.)|November 30, 2019
ChaosNet: A chaos based artificial neural network architecture for classificationHarikrishnan Nellippallil Balakrishnan, Aditi Kathpalia, Snehanshu Saha, et al.
Methods (San Diego, Calif.)|November 20, 2025
Toward accurate breast cancer classification: A review of multi-modal machine learning approachesArchana Mathur, Abbas Mufaddal Dudhiyawala, Sudeepa Roy Dey, et al.
The European Physical Journal. Special Topics|November 16, 2020
Evolution of novel activation functions in neural network training for astronomy data: habitability classification of exoplanetsSnehanshu Saha, Nithin Nagaraj, Archana Mathur, et al.
Briefings in Functional Genomics|April 30, 2024
Breast cancer prognosis through the use of multi-modal classifiers: current state of the art and the way forwardArchana Mathur, Nikhilanand Arya, Kitsuchart Pasupa, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|September 8, 2021
LipGene: Lipschitz Continuity Guided Adaptive Learning Rates for Fast Convergence on Microarray Expression Data SetsTejas Prashanth, Snehanshu Saha, Sumedh Basarkod, et al.
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