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Sanjay Saxena

Explore the profile of Sanjay Saxena including associated specialties, affiliations and a list of published articles. Areas
Snapshot
Articles 33
Citations 334
Followers 0
Related Specialties
Radiology
General Medicine
Oncology
Top 10 Co-Authors
Luca Saba
Jasjit S Suri
Sudip Paul
John R Laird
Biswajit Jena
Mostafa M Fouda
Narendra N Khanna
Shantanu Belwal
Kosmas I Paraskevas
Omender Singh
Published In
Diagnostics (Basel)
Comput Biol Med
Indian J Crit Care Med
Cancers (Basel)
Saudi J Kidney Dis Transpl
Affiliations
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Recent Articles
1.
Optimizing Glioblastoma, IDH-wildtype Treatment Outcomes : A Radiomics and Support Vector Machine-Based Approach to Overall Survival Estimation
Chong J, Jain P, Prasad S, Dubey N, Saxena S, Lo W
J Korean Neurosurg Soc . 2024 Aug; 68(1):7-18. PMID: 39099033
Objective: Glioblastoma multiforme (GBM), particularly the isocitrate dehydrogenase (IDH)-wildtype type, represents a significant clinical challenge due to its aggressive nature and poor prognosis. Despite advancements in medical imaging and its...
2.
COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography
Agarwal S, Saxena S, Carriero A, Chabert G, Ravindran G, Paul S, et al.
Front Artif Intell . 2024 Jul; 7:1304483. PMID: 39006802
Background And Novelty: When RT-PCR is ineffective in early diagnosis and understanding of COVID-19 severity, Computed Tomography (CT) scans are needed for COVID diagnosis, especially in patients having high ground-glass...
3.
AI-driven estimation of O6 methylguanine-DNA-methyltransferase (MGMT) promoter methylation in glioblastoma patients: a systematic review with bias analysis
Samartha M, Dubey N, Jena B, Maheswar G, Lo W, Saxena S
J Cancer Res Clin Oncol . 2024 Jan; 150(2):57. PMID: 38291266
Background: Accurate and non-invasive estimation of MGMT promoter methylation status in glioblastoma (GBM) patients is of paramount clinical importance, as it is a predictive biomarker associated with improved overall survival...
4.
Deep Learning Paradigm and Its Bias for Coronary Artery Wall Segmentation in Intravascular Ultrasound Scans: A Closer Look
Kumari V, Kumar N, Kumar K S, Kumar A, Skandha S, Saxena S, et al.
J Cardiovasc Dev Dis . 2023 Dec; 10(12). PMID: 38132653
Background And Motivation: Coronary artery disease (CAD) has the highest mortality rate; therefore, its diagnosis is vital. Intravascular ultrasound (IVUS) is a high-resolution imaging solution that can image coronary arteries,...
5.
Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation
Saxena S, Jena B, Mohapatra B, Gupta N, Kalra M, Scartozzi M, et al.
Comput Biol Med . 2023 Jan; 153:106492. PMID: 36621191
Background: The O6-methylguanine-DNA methyltransferase (MGMT) is a deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential clinical brain tumor biomarker for Glioblastoma Multiforme (GBM). Knowing the status...
6.
Effect of learning parameters on the performance of the U-Net architecture for cell nuclei segmentation from microscopic cell images
Jena B, Digdarshi D, Paul S, Nayak G, Saxena S
Microscopy (Oxf) . 2022 Nov; 72(3):249-264. PMID: 36409001
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 enormous variability of staining,...
7.
Recommender System for the Efficient Treatment of COVID-19 Using a Convolutional Neural Network Model and Image Similarity
Kuanr M, Mohapatra P, Mittal S, Maindarkar M, Fauda M, Saba L, et al.
Diagnostics (Basel) . 2022 Nov; 12(11). PMID: 36359545
: Hospitals face a significant problem meeting patients' medical needs during epidemics, especially when the number of patients increases rapidly, as seen during the recent COVID-19 pandemic. This study designs...
8.
Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework
Jena B, Saxena S, Nayak G, Balestrieri A, Gupta N, Khanna N, et al.
Cancers (Basel) . 2022 Aug; 14(16). PMID: 36011048
Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis....
9.
Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson's Disease Affected by COVID-19: A Narrative Review
Suri J, Maindarkar M, Paul S, Ahluwalia P, Bhagawati M, Saba L, et al.
Diagnostics (Basel) . 2022 Jul; 12(7). PMID: 35885449
: Parkinson's disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD...
10.
Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine
Saxena S, Jena B, Gupta N, Das S, Sarmah D, Bhattacharya P, et al.
Cancers (Basel) . 2022 Jun; 14(12). PMID: 35740526
Radiogenomics, a combination of "Radiomics" and "Genomics," using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data...