Sitara Afzal

1.2k total citations · 1 hit paper
16 papers, 782 citations indexed

About

Sitara Afzal is a scholar working on Artificial Intelligence, Management Science and Operations Research and Economics and Econometrics. According to data from OpenAlex, Sitara Afzal has authored 16 papers receiving a total of 782 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Management Science and Operations Research and 4 papers in Economics and Econometrics. Recurrent topics in Sitara Afzal's work include Stock Market Forecasting Methods (5 papers), Market Dynamics and Volatility (4 papers) and Machine Learning in Healthcare (2 papers). Sitara Afzal is often cited by papers focused on Stock Market Forecasting Methods (5 papers), Market Dynamics and Volatility (4 papers) and Machine Learning in Healthcare (2 papers). Sitara Afzal collaborates with scholars based in South Korea, Pakistan and United Kingdom. Sitara Afzal's co-authors include Muazzam Maqsood, Irfan Mehmood, Jong Weon Lee, Farhan Aadil, Oh-Young Song, Seungmin Rho, Junaid Baber, Sarah Gul, Attiq Ur Rehman and Rehan Ashraf and has published in prestigious journals such as IEEE Access, Sensors and RSC Advances.

In The Last Decade

Sitara Afzal

16 papers receiving 738 citations

Hit Papers

align trajectories sort by overperformance

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.

Human Activity Recognition via Hybrid Deep Learning Based Model

2022 146 citations Sitara Afzal, Jong Weon Lee et al. Sensors profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sitara Afzal South Korea	12	323	193	162	130	121	16	782
Shahan Yamin Siddiqui Pakistan	13	269 0.8×	105 0.5×	121 0.7×	15 0.1×	18 0.1×	23	734
Syed Hamad Shirazi Pakistan	13	203 0.6×	310 1.6×	57 0.4×	13 0.1×	23 0.2×	38	645
Faten S. Alamri Saudi Arabia	12	164 0.5×	105 0.5×	125 0.8×	8 0.1×	25 0.2×	52	527
Mohammad Kamrul Hasan Bangladesh	9	130 0.4×	72 0.4×	70 0.4×	10 0.1×	32 0.3×	38	515
Amal Al‐Rasheed Saudi Arabia	14	194 0.6×	83 0.4×	36 0.2×	37 0.3×	10 0.1×	60	572
Ismail Hmeidi Jordan	14	428 1.3×	92 0.5×	40 0.2×	5 0.0×	50 0.4×	44	746
Dragica Radosav Serbia	9	189 0.6×	103 0.5×	28 0.2×	15 0.1×	14 0.1×	39	575
Abdulkareem Alzahrani Saudi Arabia	11	179 0.6×	126 0.7×	61 0.4×	62 0.5×	7 0.1×	39	501
Sriparna Saha India	17	768 2.4×	117 0.6×	45 0.3×	12 0.1×	24 0.2×	110	1.1k
Ihab Zaqout Palestinian Territory	11	269 0.8×	74 0.4×	48 0.3×	33 0.3×	15 0.1×	23	466

Countries citing papers authored by Sitara Afzal

Since Specialization

Citations

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

Fields of papers citing papers by Sitara Afzal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sitara Afzal

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

All Works

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16 of 16 papers shown

Ali, Zeeshan, Jihoon Moon, Saira Gillani, et al.. (2025). Vision-based approach to knee osteoarthritis and Parkinson’s disease detection utilizing human gait patterns. PeerJ Computer Science. 11. e2857–e2857. 1 indexed citations

Rabani, Iqra, Jewon Lee, Hai Bang Truong, et al.. (2024). Construction of a uniform zeolitic imidazole framework (ZIF-8) nanocrystal through a wet chemical route towards supercapacitor application. RSC Advances. 14(1). 118–130. 19 indexed citations

Afzal, Sitara, H.A. Khan, & Jong Weon Lee. (2024). PlantView: Integrating deep learning with 3D modeling for indoor plant augmentation. Ecological Informatics. 84. 102899–102899. 1 indexed citations

Afzal, Sitara, H.A. Khan, Md. Jalil Piran, & Jong Weon Lee. (2024). A Comprehensive Survey on Affective Computing: Challenges, Trends, Applications, and Future Directions. IEEE Access. 12. 96150–96168. 13 indexed citations

Afzal, Sitara, et al.. (2024). Leveraging Augmented Reality, Semantic-Segmentation, and VANETs for Enhanced Driver’s Safety Assistance. Computers, materials & continua/Computers, materials & continua (Print). 78(1). 1443–1460. 2 indexed citations

Afzal, Sitara, et al.. (2022). Human Activity Recognition via Hybrid Deep Learning Based Model. Sensors. 22(1). 323–323. 146 indexed citations breakdown →

Afzal, Sitara, et al.. (2021). An LSTM Based Forecasting for Major Stock Sectors Using COVID Sentiment. Computers, materials & continua/Computers, materials & continua (Print). 67(1). 1191–1206. 12 indexed citations

Afzal, Sitara, et al.. (2021). An Efficient False-Positive Reduction System for Cerebral Microbleeds Detection. Computers, materials & continua/Computers, materials & continua (Print). 66(3). 2301–2315. 6 indexed citations

Afzal, Sitara, Muazzam Maqsood, Umair Khan, et al.. (2021). Alzheimer Disease Detection Techniques and Methods: A Review.. International Journal of Interactive Multimedia and Artificial Intelligence. 6(7). 26–38. 35 indexed citations

10.

Ashraf, Rehan, Sitara Afzal, Attiq Ur Rehman, et al.. (2020). Region-of-Interest Based Transfer Learning Assisted Framework for Skin Cancer Detection. IEEE Access. 8. 147858–147871. 169 indexed citations

11.

Afzal, Sitara, et al.. (2020). An Efficient Deep Learning Based Model to Predict Interest Rate Using Twitter Sentiment. Sustainability. 12(4). 1660–1660. 15 indexed citations

12.

Attique, Muhammad, et al.. (2020). Deep-learning-assisted business intelligence model for cryptocurrency forecasting using social media sentiment. Journal of Enterprise Information Management. 36(3). 718–733. 21 indexed citations

13.

Maqsood, Muazzam, et al.. (2020). A deep feature-based real-time system for Alzheimer disease stage detection. Multimedia Tools and Applications. 80(28-29). 35789–35807. 102 indexed citations

14.

Durrani, Mehr Yahya, Sitara Afzal, Muazzam Maqsood, et al.. (2019). An Intelligent Event-Sentiment-Based Daily Foreign Exchange Rate Forecasting System. Applied Sciences. 9(15). 2980–2980. 33 indexed citations

15.

Mehmood, Irfan, Muazzam Maqsood, Sitara Afzal, et al.. (2019). A local and global event sentiment based efficient stock exchange forecasting using deep learning. International Journal of Information Management. 50. 432–451. 110 indexed citations

16.

Afzal, Sitara, Muazzam Maqsood, Umair Khan, et al.. (2019). A Data Augmentation-Based Framework to Handle Class Imbalance Problem for Alzheimer’s Stage Detection. IEEE Access. 7. 115528–115539. 97 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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