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[HTML][HTML] Brain tumor characterization using radiogenomics in artificial intelligence framework
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 …
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
Abstract Background The O6-methylguanine-DNA methyltransferase (MGMT) is a
deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential …
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 …
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 …
promoters that correlates with the effectiveness of standard therapy for patients suffering …
The flux operator
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 …
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
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 …
analysis. However, robust and accurate cell nuclei segmentation is challenging due to the …
Streaming traffic classification: a hybrid deep learning and big data approach
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 …
exponential growth of applications. Analyzing patterns in generated flow traffic streaming …
The flux operator
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 …
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 …
leakage, very little research exists on the neural network model performance with applied …
Clinical applications implementation in neuro-oncology using machine learning approaches
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 …
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
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 …
the need to differentiate subtle class distinctions with limited data. This paper presents a …