Gopal Singh Tandel

@vitbhopal.ac.in

Assistant Professor
VIT Bhopal University



              

https://researchid.co/gtandel

I am currently working as Assistant Professor at VIT Bhopal University. I have completed a Ph.D. (Full Time) degree from the Department of Computer Science and Engineering, Visvesvaraya National Institute of Technology, Nagpur. So far, I have published Five SCI-indexed papers, and their citation score is 302+. I obtained BE and MTech degrees in Computer Science and Engineering in the year June-2005 and Dec-2008, respectively from RGPV University Bhopal (M.P.). I started my career in education in August 2005 and worked in various esteemed educational institutes such as SV Polytechnic Bhopal, LNCT Bhopal, AITR Bhopal, NIIST Bhopal, OP Jindal University Raigarh (Chhattishgarh), and VNIT Nagpur, I have 17+ years of experience which includes 13 years of teaching and 4+ years of research. My area of interest is to create a conducive environment for imparting quality education with the spirit of service to the nation and humanity. I believe in motivating students to achieve excellence in educ

RESEARCH INTERESTS

Health care, deep learning , Machine learning, Digital Image Processing

9

Scopus Publications

980

Scholar Citations

8

Scholar h-index

8

Scholar i10-index

Scopus Publications

  • Simulation and review of blood smear image-based leukemia classification using machine learning methods
    Gopal Singh Tandel, Nitin Kumar Mishra, and Vivek Sharma
    IOP Publishing

  • Heart Disease Prediction Using Ensemble Techniques and Explainable AI Validation
    Hardik Dulani, Uday H. Nambissan, Naman Gupta, Gagan Verma, Harshit Jaiswal, Abhishek Kumar Gupta, Swagat Kumar Samantaray, and Gopal S.Tandel
    Springer Nature Switzerland

  • Role of Ensemble Deep Learning for Brain Tumor Classification in Multiple Magnetic Resonance Imaging Sequence Data
    Gopal S. Tandel, Ashish Tiwari, Omprakash G. Kakde, Neha Gupta, Luca Saba, and Jasjit S. Suri
    MDPI AG
    The biopsy is a gold standard method for tumor grading. However, due to its invasive nature, it has sometimes proved fatal for brain tumor patients. As a result, a non-invasive computer-aided diagnosis (CAD) tool is required. Recently, many magnetic resonance imaging (MRI)-based CAD tools have been proposed for brain tumor grading. The MRI has several sequences, which can express tumor structure in different ways. However, a suitable MRI sequence for brain tumor classification is not yet known. The most common brain tumor is ‘glioma’, which is the most fatal form. Therefore, in the proposed study, to maximize the classification ability between low-grade versus high-grade glioma, three datasets were designed comprising three MRI sequences: T1-Weighted (T1W), T2-weighted (T2W), and fluid-attenuated inversion recovery (FLAIR). Further, five well-established convolutional neural networks, AlexNet, VGG16, ResNet18, GoogleNet, and ResNet50 were adopted for tumor classification. An ensemble algorithm was proposed using the majority vote of above five deep learning (DL) models to produce more consistent and improved results than any individual model. Five-fold cross validation (K5-CV) protocol was adopted for training and testing. For the proposed ensembled classifier with K5-CV, the highest test accuracies of 98.88 ± 0.63%, 97.98 ± 0.86%, and 94.75 ± 0.61% were achieved for FLAIR, T2W, and T1W-MRI data, respectively. FLAIR-MRI data was found to be most significant for brain tumor classification, where it showed a 4.17% and 0.91% improvement in accuracy against the T1W-MRI and T2W-MRI sequence data, respectively. The proposed ensembled algorithm (MajVot) showed significant improvements in the average accuracy of three datasets of 3.60%, 2.84%, 1.64%, 4.27%, and 1.14%, respectively, against AlexNet, VGG16, ResNet18, GoogleNet, and ResNet50.

  • MRI based brain tumor classification and its validation: A transfer learning paradigm




  • A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence
    Jasjit S. Suri, Sushant Agarwal, Suneet K. Gupta, Anudeep Puvvula, Mainak Biswas, Luca Saba, Arindam Bit, Gopal S. Tandel, Mohit Agarwal, Anubhav Patrick,et al.
    Elsevier BV

  • Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
    Gopal S. Tandel, Antonella Balestrieri, Tanay Jujaray, Narender N. Khanna, Luca Saba, and Jasjit S. Suri
    Elsevier BV

  • A review on a deep learning perspective in brain cancer classification
    Gopal S. Tandel, Mainak Biswas, Omprakash G. Kakde, Ashish Tiwari, Harman S. Suri, Monica Turk, John Laird, Christopher Asare, Annabel A. Ankrah, N. N. Khanna,et al.
    MDPI AG
    A World Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, and Wilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm.

RECENT SCHOLAR PUBLICATIONS

  • Multi-Class Brain Tumor Grades Classification Using a Deep Learning-Based Majority Voting Algorithm and Its Validation Using Explainable-AI
    GS Tandel, A Tiwari, OG Kakde
    Journal of Imaging Informatics in Medicine, 1-38 2025

  • Simulation and review of blood smear image-based leukemia classification using machine learning methods
    GS Tandel, NK Mishra, V Sharma
    Artificial Intelligence: A tool for effective diagnostics, 11-1-11-16 2024

  • Heart Disease Prediction Using Ensemble Techniques and Explainable AI Validation
    SKSGST Hardik Dulani, Uday H. Nambissan, Naman Gupta, Gagan Verma, Harshit ...
    Machine Intelligence, Tools, and Applications (ICMITA 2024) 2024

  • Heart Disease Prediction Using Ensemble Techniques and Explainable AI Validation
    AK Gupta, SK Samantaray, GS Tandel
    Machine Intelligence, Tools, and Applications: Proceedings of the 2024

  • Role of ensemble deep learning for brain tumor classification in multiple magnetic resonance imaging sequence data
    GS Tandel, A Tiwari, OG Kakde, N Gupta, L Saba, JS Suri
    Diagnostics 13 (3), 481 2023

  • MRI based brain tumor classification and its validation: a transfer learning paradigm
    L Saba, GS Tandel, M Biswas, M Porcu, NN Khanna, M Turk, CK Asare, ...
    Multimodality Imaging, Volume 1: Deep learning applications, 4-1-4-36 2022

  • Performance enhancement of MRI-based brain tumor classification using suitable segmentation method and deep learning-based ensemble algorithm
    GS Tandel, A Tiwari, OG Kakde
    Biomedical signal processing and control 78, 104018 2022

  • Performance optimisation of deep learning models using majority voting algorithm for brain tumour classification
    GS Tandel, A Tiwari, OG Kakde
    Computers in Biology and Medicine 135, 104564 2021

  • A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence
    JS Suri, S Agarwal, SK Gupta, A Puvvula, M Biswas, L Saba, A Bit, ...
    Computers in Biology and Medicine 130, 104210 2021

  • Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
    GS Tandel, A Balestrieri, T Jujaray, NN Khanna, L Saba, JS Suri
    Computers in Biology and Medicine 122, 103804 2020

  • A Review on a Deep Learning Perspective in Brain
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
    Application of Bioinformatics in Cancers, 373 2019

  • A review on a deep learning perspective in brain cancer classification
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
    Cancers 11 (1), 111 2019

  • A review on a deep learning perspective in brain cancer classification. Cancers (Basel) 11 (1): 111
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
     2019

  • A survey on query processing and optimization in relational database management system
    S Gupta, GS Tandel, U Pandey
    International Journal of Latest Trends in Engineering and Technology (IJLTET 2015

  • Ear Recognition
    GS Tandel
    Proceedings of International Conference on Innovation & Research in 2012

  • Survey Report On Ear Biometrics System
    GS Tandel, S Gupta, A Bhansali
    International Journal of Advanced Technology & Engineering Research (IJATER 2012

  • Human Recognition through Ear Biometrics using Average Ear Approach
    GS Tandel, S Mukherjee, O prakash Patel

  • CAPTCHA-to Enhance the Security in WWW
    A Dandapat, AS Chandel, GS Tandel

  • AStudy OF CLOUD COMPUTING THROUGH ENVIRONMENT FRIENDLY LOAD BALANCING APPROACH
    GS Tandel, U Pandey, AK Dandapat

  • A Survey on Query Processing and Optimization in Relational Database Management System
    GS Tandel, U Pandey

MOST CITED SCHOLAR PUBLICATIONS

  • A review on a deep learning perspective in brain cancer classification
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
    Cancers 11 (1), 111 2019
    Citations: 445

  • Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
    GS Tandel, A Balestrieri, T Jujaray, NN Khanna, L Saba, JS Suri
    Computers in Biology and Medicine 122, 103804 2020
    Citations: 232

  • Performance optimisation of deep learning models using majority voting algorithm for brain tumour classification
    GS Tandel, A Tiwari, OG Kakde
    Computers in Biology and Medicine 135, 104564 2021
    Citations: 97

  • A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence
    JS Suri, S Agarwal, SK Gupta, A Puvvula, M Biswas, L Saba, A Bit, ...
    Computers in Biology and Medicine 130, 104210 2021
    Citations: 80

  • Role of ensemble deep learning for brain tumor classification in multiple magnetic resonance imaging sequence data
    GS Tandel, A Tiwari, OG Kakde, N Gupta, L Saba, JS Suri
    Diagnostics 13 (3), 481 2023
    Citations: 67

  • Performance enhancement of MRI-based brain tumor classification using suitable segmentation method and deep learning-based ensemble algorithm
    GS Tandel, A Tiwari, OG Kakde
    Biomedical signal processing and control 78, 104018 2022
    Citations: 31

  • A review on a deep learning perspective in brain cancer classification. Cancers (Basel) 11 (1): 111
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
     2019
    Citations: 14

  • A survey on query processing and optimization in relational database management system
    S Gupta, GS Tandel, U Pandey
    International Journal of Latest Trends in Engineering and Technology (IJLTET 2015
    Citations: 10

  • Ear Recognition
    GS Tandel
    Proceedings of International Conference on Innovation & Research in 2012
    Citations: 2

  • A Review on a Deep Learning Perspective in Brain
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
    Application of Bioinformatics in Cancers, 373 2019
    Citations: 1

  • Survey Report On Ear Biometrics System
    GS Tandel, S Gupta, A Bhansali
    International Journal of Advanced Technology & Engineering Research (IJATER 2012
    Citations: 1

Publications

1. Tandel, G.S., Tiwari, A. and Kakde, O.G., (2022). Performance enhancement of MRI-based brain tumor classification using suitable segmentation method and deep learning-based ensemble algorithm. Biomedical Signal Processing and Control, 78, p.104018. (SCIE, IF:5.076), DOI:
2. Tandel, G.S., Tiwari, A. and Kakde, O.G., (2021). Performance Optimisation of Deep Learning Models using Majority Voting Algorithm for Brain Tumour Classification. Computers in Biology and Medicine, p.104564. (SCI, IF:4.59),
DOI:
3. Suri, J.S., Agarwal, S., Gupta, S.K., Puvvula, A., Biswas, M., Saba, L., Bit, A., Tandel, G.S., Agarwal, M., Patrick, A. and Faa, G., (2021). A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence. Computers in Biology and Medicine, p.104210. (SCI, IF:4.59),
DOI:
4. Tandel, G.S., Balestrieri, A., Jujaray, T., Khanna, N.N., Saba, L. and Suri, J.S., (2020). Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm. Computers in Biology and Medicine, 122, p.103804. (SCI, IF:4.59), DOI:
5. Tandel, G.S., Biswas, M., Kakde, O.G., Tiwari, A., Suri, H.S., Turk, M., Laird, J.R., Asare, C.K., Ankrah, A.A., Khanna, N.N. and Madhusudhan, B.K., (2019). A review on a deep learn