Kashfia Sailunaz

951 total citations · 1 hit paper
17 papers, 604 citations indexed

About

Kashfia Sailunaz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Kashfia Sailunaz has authored 17 papers receiving a total of 604 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Kashfia Sailunaz's work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Emotion and Mood Recognition (3 papers). Kashfia Sailunaz is often cited by papers focused on AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Emotion and Mood Recognition (3 papers). Kashfia Sailunaz collaborates with scholars based in Canada, Türkiye and Denmark. Kashfia Sailunaz's co-authors include Reda Alhajj, Jon Rokne, Khondaker A. Mamun, Musaed Alhussein, Tansel Özyer, Md. Sadequl Islam, Farzana Anowar, Jalal Kawash, Mohammad Nurul Huda and Suresh Neethirajan and has published in prestigious journals such as PLoS ONE, Sustainability and Future Generation Computer Systems.

In The Last Decade

Kashfia Sailunaz

15 papers receiving 571 citations

Hit Papers

Emotion and sentiment analysis from Twitter text 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Emotion and sentiment analysis from Twitter text
    2019 255 citations Kashfia Sailunaz, Reda Alhajj Journal of Computational Science profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kashfia Sailunaz Canada 9 342 114 98 86 76 17 604
K. M. Azharul Hasan Bangladesh 13 401 1.2× 53 0.5× 115 1.2× 29 0.3× 70 0.9× 109 619
Hongpo Zhang China 14 357 1.0× 37 0.3× 51 0.5× 48 0.6× 26 0.3× 39 778
Hugo Gonçalo Oliveira Portugal 13 395 1.2× 20 0.2× 64 0.7× 49 0.6× 80 1.1× 92 611
Jamil Hussain South Korea 14 299 0.9× 67 0.6× 68 0.7× 47 0.5× 148 1.9× 67 761
Md Rafiqul Islam Australia 9 172 0.5× 19 0.2× 112 1.1× 134 1.6× 47 0.6× 30 477
Kinjal Adhvaryu India 5 301 0.9× 88 0.8× 34 0.3× 33 0.4× 83 1.1× 11 443
Francisca Adoma Acheampong Ghana 4 377 1.1× 112 1.0× 71 0.7× 64 0.7× 37 0.5× 5 576
Erdenebileg Batbaatar South Korea 8 181 0.5× 66 0.6× 33 0.3× 21 0.2× 45 0.6× 16 325
Ankita Gandhi India 7 302 0.9× 89 0.8× 56 0.6× 50 0.6× 85 1.1× 17 507
Stanisław Saganowski Poland 11 161 0.5× 201 1.8× 20 0.2× 22 0.3× 64 0.8× 28 573

Countries citing papers authored by Kashfia Sailunaz

Since Specialization
Citations

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

Fields of papers citing papers by Kashfia Sailunaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kashfia Sailunaz

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

All Works

17 of 17 papers shown
1.
Sailunaz, Kashfia, et al.. (2025). Adapting the Cool Farm Tool for Achieving Net-Zero Emissions in Agriculture in Atlantic Canada. Sustainability. 17(21). 9428–9428.
2.
Sailunaz, Kashfia, et al.. (2025). Socializing AI: Integrating Social Network Analysis and Deep Learning for Precision Dairy Cow Monitoring—A Critical Review. Animals. 15(13). 1835–1835. 2 indexed citations
3.
Sailunaz, Kashfia, et al.. (2024). A survey of artificial intelligence/machine learning-based trends for prostate cancer analysis. Network Modeling Analysis in Health Informatics and Bioinformatics. 13(1).
4.
Sailunaz, Kashfia, et al.. (2023). A survey on brain tumor image analysis. Medical & Biological Engineering & Computing. 62(1). 1–45. 23 indexed citations
5.
Sailunaz, Kashfia, et al.. (2023). CNN-Transformer based emotion classification from facial expressions and body gestures. Multimedia Tools and Applications. 83(8). 23129–23171. 10 indexed citations
6.
Sailunaz, Kashfia, et al.. (2023). A Comparative Study of Different Pre-Trained Deep Learning Models and Custom CNN for Pancreatic Tumor Detection. The International Arab Journal of Information Technology. 20(3A). 11 indexed citations
7.
8.
Sailunaz, Kashfia, Tansel Özyer, Jon Rokne, & Reda Alhajj. (2023). A survey of machine learning-based methods for COVID-19 medical image analysis. Medical & Biological Engineering & Computing. 61(6). 1257–1297. 19 indexed citations
9.
Sailunaz, Kashfia, et al.. (2022). Interactive framework for Covid-19 detection and segmentation with feedback facility for dynamically improved accuracy and trust. PLoS ONE. 17(12). e0278487–e0278487. 1 indexed citations
10.
Sailunaz, Kashfia, et al.. (2022). A Multi-Modal Emotion Recognition System Based on CNN-Transformer Deep Learning Technique. University of Southern Denmark Research Portal (University of Southern Denmark). 145–150. 5 indexed citations
11.
Sailunaz, Kashfia, et al.. (2022). Pancreatic Tumor Detection by Convolutional Neural Networks. University of Southern Denmark Research Portal (University of Southern Denmark). 1–6. 3 indexed citations
12.
Sailunaz, Kashfia, Jalal Kawash, & Reda Alhajj. (2022). Tweet and user validation with supervised feature ranking and rumor classification. Multimedia Tools and Applications. 81(22). 31907–31927. 4 indexed citations
13.
Sailunaz, Kashfia & Reda Alhajj. (2019). Emotion and sentiment analysis from Twitter text. Journal of Computational Science. 36. 101003–101003. 255 indexed citations breakdown →
14.
Sailunaz, Kashfia, et al.. (2018). Emotion detection from text and speech: a survey. Social Network Analysis and Mining. 8(1). 162 indexed citations
15.
Sailunaz, Kashfia, et al.. (2016). CMED: Cloud based medical system framework for rural health monitoring in developing countries. Computers & Electrical Engineering. 53. 469–481. 29 indexed citations
16.
Mamun, Khondaker A., Musaed Alhussein, Kashfia Sailunaz, & Md. Sadequl Islam. (2015). Cloud based framework for Parkinson’s disease diagnosis and monitoring system for remote healthcare applications. Future Generation Computer Systems. 66. 36–47. 59 indexed citations
17.
Sailunaz, Kashfia, et al.. (2014). Data Compression Considering Text Files. International Journal of Computer Applications. 90(11). 27–32. 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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