[HTML][HTML] Brain tumor characterization using radiogenomics in artificial intelligence framework

B Jena, S Saxena, GK Nayak, A Balestrieri, N Gupta… - Cancers, 2022 - mdpi.com
Simple Summary Radiogenomics is a relatively new advancement in the understanding of
the biology and behaviour of cancer in response to conventional treatments. One of the most …

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: a neuro-oncological investigation

S Saxena, B Jena, B Mohapatra, N Gupta… - Computers in Biology …, 2023 - Elsevier
Abstract Background The O6-methylguanine-DNA methyltransferase (MGMT) is a
deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential …

Prediction of O-6-methylguanine-DNA methyltransferase and overall survival of the patients suffering from glioblastoma using MRI-based hybrid radiomics signatures …

S Saxena, A Agrawal, P Dash, B Jena… - Neural Computing and …, 2023 - Springer
Abstract O-6-methylguanine-DNA methyltransferase (MGMT) is one of the most salient gene
promoters that correlates with the effectiveness of standard therapy for patients suffering …

The flux operator

V Sochat, A Culquicondor, A Ojea, D Milroy - F1000Research, 2024 - pmc.ncbi.nlm.nih.gov
Converged computing is an emerging area of computing that brings together the best of both
worlds for high performance computing (HPC) and cloud-native communities. The economic …

Effect of learning parameters on the performance of the U-Net architecture for cell nuclei segmentation from microscopic cell images

B Jena, D Digdarshi, S Paul, GK Nayak, S Saxena - Microscopy, 2023 - academic.oup.com
Nuclei segmentation of cells is the preliminary and essential step of pathological image
analysis. However, robust and accurate cell nuclei segmentation is challenging due to the …

Streaming traffic classification: a hybrid deep learning and big data approach

M Seydali, F Khunjush, J Dogani - Cluster Computing, 2024 - Springer
Massive amounts of real-time streaming network data are generated quickly because of the
exponential growth of applications. Analyzing patterns in generated flow traffic streaming …

The flux operator

V Sochat, A Culquicondor, A Ojea, D Milroy - arxiv preprint arxiv …, 2023 - arxiv.org
Converged computing brings together the best of both worlds for high performance
computing (HPC) and cloud-native communities. In fact, the economic impact of cloud …

[HTML][HTML] Application of differential privacy to sensor data in water quality monitoring task

A Arzovs, S Parshutin, V Urbanovics, J Rubulis… - Ecological …, 2025 - Elsevier
Although differential privacy (DP) is used to obfuscate local information and avoid data
leakage, very little research exists on the neural network model performance with applied …

Clinical applications implementation in neuro-oncology using machine learning approaches

B Jena, I Ayus, S Saxena - Radiomics and Radiogenomics in Neuro …, 2024 - Elsevier
Neuro-oncology is a field that is rapidly advancing and involves the identification and
management of tumors in the brain and spinal cord. As more and more patient data become …

Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learning

E Brouwer, JE van Woerden, G Burghouts… - arxiv preprint arxiv …, 2024 - arxiv.org
Few-shot, fine-grained classification in computer vision poses significant challenges due to
the need to differentiate subtle class distinctions with limited data. This paper presents a …