Gopal Singh Tandel

@vitbhopal.ac.in

Assistant Professor
VIT Bhopal University

Gopal Singh Tandel


               Download Compact PDF  
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
11

Scopus Publications

1301

Scholar Citations

9

Scholar h-index

9

Scholar i10-index

Scopus Publications

  • Multi-Class Brain Tumor Grades Classification Using a Deep Learning-Based Majority Voting Algorithm and Its Validation Using Explainable-AI
    Gopal Singh Tandel, Ashish Tiwari, Omprakash G. Kakde
    Journal of Imaging Informatics in Medicine, 2025
  • Recent Developments and Applications of Digital Technologies in Healthcare Systems
    Swagat Kumar Samantaray, Gopal Singh Tandel, Shasanka Sekhar Rout
    Smart Electronics Devices and Models for Healthcare Systems, 2025
    Recently, digital technology has had a tremendous impact on the healthcare system to increase the quality of care. The adoption of various digital technologies has an effect on various healthcare systems. Digital technology developments strive to reduce time, enhance accuracy and efficiency, and combine technologies in creative ways in healthcare. The World Health Organization (WHO) emphasizes the importance of carefully considering the quality of care and health services. According to WHO, the use of information and communications technologies for health is known as eHealth, or digital health. In this chapter, we focused on various digital technologies that can provide physical, cognitive, and most essential social support for the healthcare systems. The digital technology encompasses various technologies, such as telehealth, which facilitates remote healthcare by utilizing digital information and communication. Wearable technology, along with the body sensors, transmits a wide range of data for patient health tracking. Recent technological advancements have accelerated the digitalization of health data and promoted the widespread adoption of electronic health record (EHR) systems. The convergence of digital technology and artificial intelligence (AI) has paved the way for precision medicine. Clinical decision support system (CDSS) provides the base for medical data analytics and is to be used for reducing medical errors. Also, the digital technology enables early detection and early diagnosis of the disease through mHealth technology. Along with the technological advancement for the healthcare systems, they also bring various challenges of privacy and data confidentiality for the healthcare. system.
  • Simulation and review of blood smear image-based leukemia classification using machine learning methods
    Gopal Singh Tandel, Nitin Kumar Mishra, Vivek Sharma
    Artificial Intelligence A Tool for Effective Diagnostics, 2024
    Chapter 11 explores the integration of advanced machine learning techniques into the detection and classification of leukemia using blood smear images. It highlights the limitations of traditional diagnostic methods in accurately distinguishing between different leukemia subtypes, emphasizing the need for more sophisticated computational approaches.
  • 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, Gopal S.Tandel
    Learning and Analytics in Intelligent Systems, 2024
  • 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, Jasjit S. Suri
    Diagnostics, 2023
    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
    Multimodality Imaging Volume 1 Deep Learning Applications, 2022
  • Performance enhancement of MRI-based brain tumor classification using suitable segmentation method and deep learning-based ensemble algorithm
    Gopal S. Tandel, Ashish Tiwari, O.G. Kakde
    Biomedical Signal Processing and Control, 2022
  • Performance optimisation of deep learning models using majority voting algorithm for brain tumour classification
    Gopal S. Tandel, Ashish Tiwari, O.G. Kakde
    Computers in Biology and Medicine, 2021
  • 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, Gavino Faa, Inder M. Singh, Ronald Oberleitner, Monika Turk, Paramjit S. Chadha, Amer M. Johri, J. Miguel Sanches, Narendra N. Khanna, Klaudija Viskovic, Sophie Mavrogeni, John R. Laird, Gyan Pareek, Martin Miner, David W. Sobel, Antonella Balestrieri, Petros P. Sfikakis, George Tsoulfas, Athanasios Protogerou, Durga Prasanna Misra, Vikas Agarwal, George D. Kitas, Puneet Ahluwalia, Jagjit Teji, Mustafa Al-Maini, Surinder K. Dhanjil, Meyypan Sockalingam, Ajit Saxena, Andrew Nicolaides, Aditya Sharma, Vijay Rathore, Janet N.A. Ajuluchukwu, Mostafa Fatemi, Azra Alizad, Vijay Viswanathan, P.K. Krishnan, Subbaram Naidu
    Computers in Biology and Medicine, 2021
  • Multiclass magnetic resonance imaging brain tumor classification using artificial intelligence paradigm
    Gopal S. Tandel, Antonella Balestrieri, Tanay Jujaray, Narender N. Khanna, Luca Saba, Jasjit S. Suri
    Computers in Biology and Medicine, 2020
  • 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, B. K. Madhusudhan, Luca Saba, Jasjit S. Suri
    Cancers, 2019

RECENT SCHOLAR PUBLICATIONS

  • Recent Developments and Applications of Digital Technologies in Healthcare Systems
    SK Samantaray, GS Tandel, SS Rout
    Smart Electronics Devices and Models for Healthcare Systems, 102-119 , 2025
    2025.0
  • 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 38 (5), 2793-2830 , 2025
    2025.0
    Citations: 13
  • Artificial Intelligence: A tool for effective diagnostics
    SK Khare, S Taran, AD Jamthikar
    IOP publishing , 2024
    2024.0
    Citations: 2
  • 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
    2024.0
  • 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
    2024.0
    Citations: 4
  • 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
    2024.0
  • 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
    2023.0
    Citations: 114
  • 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
    2022.0
  • 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
    2022.0
    Citations: 40
  • 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
    2021.0
    Citations: 138
  • 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
    2021.0
    Citations: 89
  • 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
    2020.0
    Citations: 305
  • 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
    2019.0
    Citations: 2
  • 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
    2019.0
    Citations: 562
  • A review on a deep learning perspective in brain cancer classification. Cancers 11 (1): 111
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
    2019.0
    Citations: 18
  • 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
    2015.0
    Citations: 11
  • Ear Recognition
    GS Tandel
    Proceedings of International Conference on Innovation & Research in … , 2012
    2012.0
    Citations: 2
  • Survey Report On Ear Biometrics System
    GS Tandel, S Gupta, A Bhansali
    International Journal of Advanced Technology & Engineering Research (IJATER … , 2012
    2012.0
    Citations: 1
  • 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

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
    2019.0
    Citations: 562
  • 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
    2020.0
    Citations: 305
  • 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
    2021.0
    Citations: 138
  • 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
    2023.0
    Citations: 114
  • 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
    2021.0
    Citations: 89
  • 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
    2022.0
    Citations: 40
  • A review on a deep learning perspective in brain cancer classification. Cancers 11 (1): 111
    GS Tandel, M Biswas, OG Kakde, A Tiwari, HS Suri, M Turk, JR Laird, ...
    2019.0
    Citations: 18
  • 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 38 (5), 2793-2830 , 2025
    2025.0
    Citations: 13
  • 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
    2015.0
    Citations: 11
  • 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
    2024.0
    Citations: 4
  • Artificial Intelligence: A tool for effective diagnostics
    SK Khare, S Taran, AD Jamthikar
    IOP publishing , 2024
    2024.0
    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
    2019.0
    Citations: 2
  • Ear Recognition
    GS Tandel
    Proceedings of International Conference on Innovation & Research in … , 2012
    2012.0
    Citations: 2
  • Survey Report On Ear Biometrics System
    GS Tandel, S Gupta, A Bhansali
    International Journal of Advanced Technology & Engineering Research (IJATER … , 2012
    2012.0
    Citations: 1
  • Recent Developments and Applications of Digital Technologies in Healthcare Systems
    SK Samantaray, GS Tandel, SS Rout
    Smart Electronics Devices and Models for Healthcare Systems, 102-119 , 2025
    2025.0
  • 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
    2024.0
  • 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
    2024.0
  • 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
    2022.0
  • 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

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