M. Sudha

407 total citations
22 papers, 212 citations indexed

About

M. Sudha is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, M. Sudha has authored 22 papers receiving a total of 212 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Information Systems and 4 papers in Computational Theory and Mathematics. Recurrent topics in M. Sudha's work include Data Mining Algorithms and Applications (5 papers), Hydrological Forecasting Using AI (4 papers) and Rough Sets and Fuzzy Logic (4 papers). M. Sudha is often cited by papers focused on Data Mining Algorithms and Applications (5 papers), Hydrological Forecasting Using AI (4 papers) and Rough Sets and Fuzzy Logic (4 papers). M. Sudha collaborates with scholars based in India, Malaysia and Egypt. M. Sudha's co-authors include A. Kumaravel, Karthik Sekaran, Mohammad Kamrul Hasan, Suliman A. Alsuhibany, S. Abdel‐Khalek, Rashid A. Saeed, Raj Rajkumar, S. Navaneethan, Sivalingam Elayabalan and S. Geetha and has published in prestigious journals such as Computer Communications, Frontiers in Public Health and Journal of Medical Systems.

In The Last Decade

M. Sudha

19 papers receiving 198 citations

Peers

M. Sudha
Thulasi Bikku India
S. Sountharrajan India
Feng-Jen Yang United States
Yousra Asim Pakistan
Yasser Omar Egypt
Sudarson Jena India
Augusto Júnio Guimarães Brazil
Vanessa Souza Araújo Brazil
Osama R. Shahin Saudi Arabia
Yun‐Huoy Choo Malaysia
Thulasi Bikku India
M. Sudha
Citations per year, relative to M. Sudha M. Sudha (= 1×) peers Thulasi Bikku

Countries citing papers authored by M. Sudha

Since Specialization
Citations

This map shows the geographic impact of M. Sudha'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 M. Sudha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Sudha more than expected).

Fields of papers citing papers by M. Sudha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Sudha. 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 M. Sudha. The network helps show where M. Sudha may publish in the future.

Co-authorship network of co-authors of M. Sudha

This figure shows the co-authorship network connecting the top 25 collaborators of M. Sudha. A scholar is included among the top collaborators of M. Sudha 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 M. Sudha. M. Sudha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Rajkumar, Raj, et al.. (2024). Enhanced Jaya Optimization Algorithm with Deep Learning Assisted Oral Cancer Diagnosis on IoT Healthcare Systems. Journal of Intelligent Systems and Internet of Things. 11(2). 97–110. 14 indexed citations
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Sudha, M., et al.. (2023). Exploring the Gradient Boosting and LSTM for Power Distribution-based Time Series Analysis. 1(4). 1–10. 2 indexed citations
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Sudha, M., et al.. (2022). An Empirical Model to Predict the Diabetic Positive Using Stacked Ensemble Approach. Frontiers in Public Health. 9. 792124–792124. 19 indexed citations
7.
Sudha, M., et al.. (2022). Convolutional Neural Network based Leaf Disease Detection. 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT). 2. 1–7. 1 indexed citations
8.
Sudha, M., et al.. (2021). Predicting heart failure using data mining with Rough set theory and Fuzzy Petri Net. Journal of Physics Conference Series. 1724(1). 12033–12033. 1 indexed citations
9.
Sudha, M., et al.. (2020). PLANT DISEASE DETECTION AND WEED CONTROL SYSTEM BY USING MACHINE LEARNING ALGORITHMS: A REVIEW. 7(19). 2178–2194. 1 indexed citations
10.
Sudha, M., et al.. (2020). Predicting bipolar disorder and schizophrenia based on non-overlapping genetic phenotypes using deep neural network. Evolutionary Intelligence. 14(2). 619–634. 24 indexed citations
11.
Sekaran, Karthik & M. Sudha. (2019). Prediction of lipopolysaccharides simulation responsiveness on gene expression profiles of major depression disorder affected cases using machine learning. 8(11). 21–24. 6 indexed citations
12.
Sekaran, Karthik & M. Sudha. (2019). Predicting drug responsiveness with deep learning from the effects on gene expression of Obsessive–Compulsive Disorder affected cases. Computer Communications. 151. 386–394. 8 indexed citations
13.
Sudha, M.. (2017). Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice. Journal of Medical Systems. 41(11). 178–178. 13 indexed citations
14.
Sudha, M. & A. Kumaravel. (2017). Analysis and Measurement of Wave Guides Using Poisson Method. Indonesian Journal of Electrical Engineering and Computer Science. 8(2). 546–546. 83 indexed citations
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Sudha, M., et al.. (2015). Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction. Agris on-line Papers in Economics and Informatics. 7(4). 151–160. 4 indexed citations
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Sudha, M., et al.. (2015). Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction. AgEcon Search (University of Minnesota, USA). 7(4). 151–160. 3 indexed citations
18.
Sudha, M. & A. Kumaravel. (2014). Performance Comparison based on Attribute Selection Tools for Data Mining. Indian Journal of Science and Technology. 7(7). 61–65. 4 indexed citations
19.
Sudha, M., et al.. (2014). Structure Based Virtual Screening and Docking Studies of the Replicase Gene of Banana Bunchy Top Virus. 2 indexed citations
20.
Sudha, M., et al.. (2014). Rainfall Forecast Analysis using Rough Set Attribute Reduction and Data Mining Methods. AgEcon Search (University of Minnesota, USA). 6(4). 145–154. 9 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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