Varsha Nemade

487 total citations
12 papers, 247 citations indexed

About

Varsha Nemade is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, Varsha Nemade has authored 12 papers receiving a total of 247 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Varsha Nemade's work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Brain Tumor Detection and Classification (2 papers). Varsha Nemade is often cited by papers focused on AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Brain Tumor Detection and Classification (2 papers). Varsha Nemade collaborates with scholars based in India. Varsha Nemade's co-authors include Sunil Pathak, Ashutosh Kumar Dubey and Vishal Fegade and has published in prestigious journals such as Archives of Computational Methods in Engineering, Microsystem Technologies and Journal of Physics Conference Series.

In The Last Decade

Varsha Nemade

12 papers receiving 226 citations

Peers

Varsha Nemade

RNMI

HIM

PRM

NEURO

Shahid Mehmood Pakistan

Krishna Mridha India

Negar Maleki United States

Fahima A. Maghraby Egypt

Yaman Afadar United Arab Emirates

Kartika Fithriasari Indonesia

Dolly Das India

Hanan S. Alghamdi Saudi Arabia

Parita Oza India

Shahid Mehmood Pakistan

Varsha Nemade

186 ×1.2

143 ×1.5

RNMI

21 ×0.6

HIM

33 ×0.9

PRM

29 ×0.9

NEURO

Citations per year, relative to Varsha Nemade Varsha Nemade (= 1×) peers Shahid Mehmood

Countries citing papers authored by Varsha Nemade

Since Specialization

Citations

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

Fields of papers citing papers by Varsha Nemade

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Varsha Nemade

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

All Works

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12 of 12 papers shown

Nemade, Varsha, Sunil Pathak, & Ashutosh Kumar Dubey. (2023). Deep learning-based ensemble model for classification of breast cancer. Microsystem Technologies. 30(5). 513–527. 9 indexed citations

Nemade, Varsha, Sunil Pathak, & Ashutosh Kumar Dubey. (2023). Hybrid Deep Convolutional Neural Network Approach for Detecting Breast Cancer in Mammography Images. International Journal of Electrical and Electronics Engineering. 10(5). 102–119. 3 indexed citations

Nemade, Varsha & Vishal Fegade. (2023). Machine Learning Techniques for Breast Cancer Prediction. Procedia Computer Science. 218. 1314–1320. 34 indexed citations

Nemade, Varsha, et al.. (2022). A Review and Computational Analysis of Breast Cancer Using Different Machine Learning Techniques. International Journal of Emerging Technology and Advanced Engineering. 12(3). 111–118. 14 indexed citations

Pathak, Sunil, et al.. (2022). Cohort study on recognition of plant species using Deep Learning methods. Journal of Physics Conference Series. 2273(1). 12006–12006. 4 indexed citations

Nemade, Varsha, Sunil Pathak, & Ashutosh Kumar Dubey. (2022). A Systematic Literature Review of Breast Cancer Diagnosis Using Machine Intelligence Techniques. Archives of Computational Methods in Engineering. 29(6). 4401–4430. 30 indexed citations

Nemade, Varsha, et al.. (2021). Prediction and Classification of Lung Cancer Using Machine Learning Techniques. IOP Conference Series Materials Science and Engineering. 1099(1). 12059–12059. 69 indexed citations

Nemade, Varsha, et al.. (2019). Comprehensive Study on Automated Image Detection by using Robotics for Agriculture Applications. 2019 3rd International conference on Electronics, Communication and Aerospace Technology (ICECA). 637–641. 5 indexed citations

Nemade, Varsha, et al.. (2018). Predictive Modelling For Credit Card Fraud Detection Using Data Analytics. Procedia Computer Science. 132. 385–395. 69 indexed citations

10.

Nemade, Varsha, et al.. (2018). Predictive Analysis using Data Mining Techniques for Heart Disease Diagnosis. International Journal of Engineering & Technology. 7(3.1). 166–166. 1 indexed citations

11.

Nemade, Varsha, et al.. (2017). Query Optimization using Modified Ant Colony Algorithm. International Journal of Computer Applications. 167(2). 29–33. 6 indexed citations

12.

Nemade, Varsha, et al.. (2017). Query Optimization using Multiple Techniques. International Journal of Computer Applications. 163(3). 30–32. 3 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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