B. V. Ramana

419 total citations
15 papers, 259 citations indexed

About

B. V. Ramana is a scholar working on Artificial Intelligence, Health Information Management and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, B. V. Ramana has authored 15 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Health Information Management and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in B. V. Ramana's work include Artificial Intelligence in Healthcare (7 papers), Brain Tumor Detection and Classification (3 papers) and COVID-19 diagnosis using AI (3 papers). B. V. Ramana is often cited by papers focused on Artificial Intelligence in Healthcare (7 papers), Brain Tumor Detection and Classification (3 papers) and COVID-19 diagnosis using AI (3 papers). B. V. Ramana collaborates with scholars based in India. B. V. Ramana's co-authors include M. S. Prasad Babu, N. Venkateswarlu, Raja Sarath Kumar Boddu, K. Ravi, Nibedan Panda, M. Venu Gopalachari, K. Srinivas, Debabrata Singh and Bandameeda Ramesh Naidu and has published in prestigious journals such as Journal of Computational and Theoretical Nanoscience, SN Computer Science and International Journal of Electrical and Computer Engineering (IJECE).

In The Last Decade

B. V. Ramana

13 papers receiving 226 citations

Peers

B. V. Ramana
Ali Samad Pakistan
Kaiping Zheng Singapore
Dola Das Bangladesh
B. V. Ramana
Citations per year, relative to B. V. Ramana B. V. Ramana (= 1×) peers Saloni Kumari

Countries citing papers authored by B. V. Ramana

Since Specialization
Citations

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

Fields of papers citing papers by B. V. Ramana

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by B. V. Ramana. 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 B. V. Ramana. The network helps show where B. V. Ramana may publish in the future.

Co-authorship network of co-authors of B. V. Ramana

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

All Works

15 of 15 papers shown
1.
Panda, Nibedan, et al.. (2025). DiagPCNN: Enhancing CNN through Pretrained Model for Brain Tumor Diagnosis. Procedia Computer Science. 258. 2334–2342.
2.
Panda, Nibedan, et al.. (2025). Automated Healthcare Medical Imaging through EOA Optimized Hyperparameter in CNN. Procedia Computer Science. 259. 1106–1114. 1 indexed citations
3.
Ramana, B. V., et al.. (2024). Leveraging LSTM and Multinomial Naive Bayes for Nuanced Textual-Based Sentiment Analysis. SN Computer Science. 5(8). 4 indexed citations
4.
Ramana, B. V., et al.. (2023). A Comparison of Pre-Trained Models for Pneumonia Disease Prediction Using Chest Images. Journal Of Advanced Zoology. 44(3). 263–270. 1 indexed citations
5.
Naidu, Bandameeda Ramesh, et al.. (2023). Toxic Comment Classification using Deep Learning. International Journal on Recent and Innovation Trends in Computing and Communication. 11(7). 93–104. 3 indexed citations
6.
Gopalachari, M. Venu, et al.. (2023). Optimizing Chronic Kidney Disease Diagnosis in Uddanam: A Smart Fusion of GA-MLP Hybrid and PCA Dimensionality Reduction. Procedia Computer Science. 230. 522–531. 4 indexed citations
7.
Ramana, B. V., et al.. (2022). Supervised Machine Learning Approaches for Medical Data Classification. 1–8. 2 indexed citations
8.
Srinivas, K., et al.. (2019). Convolution Neural Networks for Binary Classification. Journal of Computational and Theoretical Nanoscience. 16(11). 4877–4882. 3 indexed citations
9.
Ramana, B. V. & Raja Sarath Kumar Boddu. (2019). Performance Comparison of Classification Algorithms on Medical Datasets. 140–145. 24 indexed citations
10.
Ramana, B. V.. (2018). Smart Helmet with Alcohol Identification, Accident Detection, and Drowsiness Detection System. International Journal for Research in Applied Science and Engineering Technology. 6(4). 363–369. 1 indexed citations
11.
Ramana, B. V., et al.. (2015). De-Identified Personal Health Care System Using Hadoop. International Journal of Electrical and Computer Engineering (IJECE). 5(6). 1492–1492. 7 indexed citations
12.
Babu, M. S. Prasad, et al.. (2013). A web-based soya bean expert system using bagging algorithm with C4.5 decision trees.. International journal of agriculture innovation and research. 1(4). 91–96. 2 indexed citations
13.
Ramana, B. V., M. S. Prasad Babu, & N. Venkateswarlu. (2012). A Critical Comparative Study of Liver Patients from USA and INDIA: An Exploratory Analysis. 9(3). 506–516. 46 indexed citations
14.
Ravi, K., et al.. (2012). Pilgrims Tracking and Identification Using RFID Technology. 1(2). 96–105. 5 indexed citations
15.
Ramana, B. V., M. S. Prasad Babu, & N. Venkateswarlu. (2011). A Critical Study of Selected Classification Algorithms for Liver Disease Diagnosis. 3(2). 101–114. 156 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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