Krishna Mridha

664 total citations
29 papers, 282 citations indexed

About

Krishna Mridha is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Krishna Mridha has authored 29 papers receiving a total of 282 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 12 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Krishna Mridha's work include COVID-19 diagnosis using AI (9 papers), AI in cancer detection (7 papers) and Artificial Intelligence in Healthcare (4 papers). Krishna Mridha is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), AI in cancer detection (7 papers) and Artificial Intelligence in Healthcare (4 papers). Krishna Mridha collaborates with scholars based in India, Bangladesh and China. Krishna Mridha's co-authors include Md. Mezbah Uddin, M. F. Mridha, Jungpil Shin, Ankush Ghosh, Rabindra Nath Shaw, Dinesh Kumar, Madhu Shukla, Ibrahim Khalil, Lijun Zhang and Md. Golam Rabbani and has published in prestigious journals such as IEEE Access, Multimedia Tools and Applications and 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON).

In The Last Decade

Krishna Mridha

26 papers receiving 259 citations

Peers

Krishna Mridha

ONCOL

EPIDE

RNMI

HIM

Mani Abedini Australia

Rehan Ashraf Pakistan

Poonam Rani India

Reinaldo Padilha França Brazil

Shahzad Mumtaz Pakistan

Bogdan Mazoure Canada

Luciano Caroprese Italy

Fahima A. Maghraby Egypt

Muhammad Mateen Yaqoob Pakistan

Tauqeer Faiz United Arab Emirates

Mani Abedini Australia

Krishna Mridha

125 ×1.1

100 ×1.4

ONCOL

29 ×0.5

EPIDE

17 ×0.4

RNMI

20 ×0.5

HIM

Citations per year, relative to Krishna Mridha Krishna Mridha (= 1×) peers Mani Abedini

Countries citing papers authored by Krishna Mridha

Since Specialization

Citations

This map shows the geographic impact of Krishna Mridha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Krishna Mridha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Krishna Mridha more than expected).

Fields of papers citing papers by Krishna Mridha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Krishna Mridha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Krishna Mridha. The network helps show where Krishna Mridha may publish in the future.

Co-authorship network of co-authors of Krishna Mridha

This figure shows the co-authorship network connecting the top 25 collaborators of Krishna Mridha. A scholar is included among the top collaborators of Krishna Mridha based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Krishna Mridha. Krishna Mridha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Mridha, Krishna, et al.. (2024). Unraveling the intricacies of EEG seizure detection: A comprehensive exploration of machine learning model performance, interpretability, and clinical insights. Multimedia Tools and Applications. 83(41). 89217–89247.

Mridha, Krishna, Ming Wang, & Lijun Zhang. (2024). AI-Driven Diagnostics in Ophthalmology: Tailored Deep Learning Models for Diabetic Retinopathy with XAI Insights. EPiC series in computing. 101. 73–62. 1 indexed citations

Mridha, Krishna, et al.. (2023). Accuracy and Interpretability: Developing a Computer-Aided Diagnosis System for Pneumonia Detection in Chest X-Ray Images.

Mridha, Krishna, et al.. (2023). An Interpretable Skin Cancer Classification Using Optimized Convolutional Neural Network for a Smart Healthcare System. IEEE Access. 11. 41003–41018. 84 indexed citations

Mridha, Krishna, et al.. (2023). Explainable Deep Learning for Coffee Leaf Disease Classification in Smart Agriculture: A Visual Approach. 1–8. 9 indexed citations

Mridha, Krishna, et al.. (2023). Attention U-Net: A Deep Learning Approach for Breast Cancer Segmentation. 1–6. 2 indexed citations

Mridha, Krishna, et al.. (2023). Automated Stroke Prediction Using Machine Learning: An Explainable and Exploratory Study With a Web Application for Early Intervention. IEEE Access. 11. 52288–52308. 36 indexed citations

Mridha, Krishna, et al.. (2022). U-Net for Medical Imaging: A Novel Approach for Brain Tumor Segmentation. 1(1). 20–28. 2 indexed citations

Mridha, Krishna, et al.. (2022). ML-DP: A Smart Emotion Detection System for Disabled Person to Develop a Smart City. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–6. 2 indexed citations

10.

Begum, Fatema, et al.. (2022). Bioactivity classification of SARS-CoV-2 Proteinase using Machine Learning Approaches. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 39. 1–6. 1 indexed citations

11.

Mridha, Krishna, et al.. (2022). Short-Term Electricity Consumption Forecasting: Time-Series Approaches. 2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 1–5. 5 indexed citations

12.

Mridha, Krishna. (2021). Early Prediction of Breast Cancer by using Artificial Neural Network and Machine Learning Techniques. 582–587. 20 indexed citations

13.

Mridha, Krishna, et al.. (2021). Temporal Features and Machine learning Approaches to Study Brain Activity with EEG and ECG. 409–414. 4 indexed citations

14.

Mridha, Krishna, et al.. (2021). Medium and Short Term Energy Forecasting using LSTM Neural Network Method for Gujarat State. 1–5. 4 indexed citations

15.

Mridha, Krishna, et al.. (2021). Deep Learning Algorithms are used to Automatically Detection Invasive Ducal Carcinoma in Whole Slide Images. 123–129. 14 indexed citations

16.

Mridha, Krishna, et al.. (2021). Study and Prediction Analysis of the Employee Turnover using Machine Learning Approaches. 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON). 1–6. 25 indexed citations

17.

Mridha, Krishna, et al.. (2021). Automatically Detect the coronavirus (COVID-19) disease using Chest X-ray and CT images. 150–156. 2 indexed citations

18.

Mridha, Krishna, et al.. (2021). Respiratory Disease Classification by CNN using MFCC. 517–523. 12 indexed citations

19.

Mridha, Krishna, et al.. (2021). Web Based Brain Tumor Detection using Neural Network. 137–143. 5 indexed citations

20.

Mridha, Krishna, et al.. (2021). Artificial Intelligence (AI) for Agricultural Sector. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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