Sadia Shakil

1.1k total citations · 1 hit paper
25 papers, 767 citations indexed

About

Sadia Shakil is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Sadia Shakil has authored 25 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cognitive Neuroscience, 10 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Biomedical Engineering. Recurrent topics in Sadia Shakil's work include Functional Brain Connectivity Studies (11 papers), Neural dynamics and brain function (10 papers) and EEG and Brain-Computer Interfaces (7 papers). Sadia Shakil is often cited by papers focused on Functional Brain Connectivity Studies (11 papers), Neural dynamics and brain function (10 papers) and EEG and Brain-Computer Interfaces (7 papers). Sadia Shakil collaborates with scholars based in United States, Pakistan and Hong Kong. Sadia Shakil's co-authors include Shella Keilholz, Chin‐Hui Lee, Khurram Khurshid, Jacob Billings, Wen‐Ju Pan, Shahab A. Shamsi, Lei Ye, Feliciano Priego‐Capote, Staffan Nilsson and Maysam Nezafati and has published in prestigious journals such as NeuroImage, Analytical Chemistry and Scientific Reports.

In The Last Decade

Sadia Shakil

22 papers receiving 744 citations

Hit Papers

Role of deep learning in brain tumor detection and classi... 2021 2026 2022 2024 2021 50 100 150
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. Role of deep learning in brain tumor detection and classification (2015 to 2020): A review
    2021 185 citations Sadia Shakil, Khurram Khurshid et al. Computerized Medical Imaging and Graphics profile →

Peers

Sadia Shakil
Xiaowei Zhuang United States
Kun‐Han Lu United States
Zhengshi Yang United States
Shuixia Guo China
Shaun Frost Australia
Muhammad Naveed Iqbal Qureshi South Korea
Sally A. Frutiger United States
Rogers F. Silva United States
Xiaowei Zhuang United States
Sadia Shakil
Citations per year, relative to Sadia Shakil Sadia Shakil (= 1×) peers Xiaowei Zhuang

Countries citing papers authored by Sadia Shakil

Since Specialization
Citations

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

Fields of papers citing papers by Sadia Shakil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sadia Shakil

This figure shows the co-authorship network connecting the top 25 collaborators of Sadia Shakil. A scholar is included among the top collaborators of Sadia Shakil 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 Sadia Shakil. Sadia Shakil 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
1.
2.
Liu, Tao, Ziwei Wang, Sadia Shakil, & Raymond Kai‐Yu Tong. (2025). Uncovering Low-Dimensional Manifolds of Neural Dynamics for Motor-Imagery Based Stroke Rehabilitation: An EEG-Based Brain–Computer Interface Study. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 33. 3281–3292.
3.
Zhou, Meng, et al.. (2025). Alzheimer's disease recognition via long-range state space model using multi-modal brain images. Frontiers in Neuroscience. 19. 1576931–1576931. 2 indexed citations
4.
Chen, Xinyi, Ye Li, Dong Liang, et al.. (2024). IG-GCN: Empowering e-Health Services for Alzheimer’s Disease Prediction. IEEE Transactions on Consumer Electronics. 70(4). 6442–6451. 5 indexed citations
5.
Shakil, Sadia, et al.. (2024). End-to-End Multi-task Learning Architecture for Brain Tumor Analysis with Uncertainty Estimation in MRI Images. Journal of Imaging Informatics in Medicine. 37(5). 2149–2172.
6.
Shakil, Sadia, et al.. (2023). Sentiments analysis of fMRI using automatically generated stimuli labels under naturalistic paradigm. Scientific Reports. 13(1). 7267–7267. 8 indexed citations
7.
Shakil, Sadia, et al.. (2023). Robust and adaptive terrain classification and gait event detection system. Heliyon. 9(11). e21720–e21720. 2 indexed citations
8.
Shakil, Sadia, et al.. (2023). EEG-based stress identification and classification using deep learning. Multimedia Tools and Applications. 83(14). 42703–42719. 13 indexed citations
9.
Ali, Muhammad Junaid, et al.. (2022). Multi-task learning architecture for brain tumor detection and segmentation in MRI images. Journal of Electronic Imaging. 31(5). 2 indexed citations
10.
Shakil, Sadia, et al.. (2021). Role of deep learning in brain tumor detection and classification (2015 to 2020): A review. Computerized Medical Imaging and Graphics. 91. 101940–101940. 185 indexed citations breakdown →
11.
Adamson, Maheen M., Sadia Shakil, Muhammad Abul Hasan, et al.. (2020). Brain Injury and Dementia in Pakistan: Current Perspectives. Frontiers in Neurology. 11. 299–299. 16 indexed citations
12.
Billings, Jacob, Sadia Shakil, Xiaohong Shen, et al.. (2017). Instantaneous brain dynamics mapped to a continuous state space. NeuroImage. 162. 344–352. 13 indexed citations
13.
Shakil, Sadia, Jacob Billings, Shella Keilholz, & Chin‐Hui Lee. (2017). Parametric Dependencies of Sliding Window Correlation. IEEE Transactions on Biomedical Engineering. 65(2). 254–263. 19 indexed citations
14.
Keilholz, Shella, Wen‐Ju Pan, Jacob Billings, Maysam Nezafati, & Sadia Shakil. (2016). Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies. NeuroImage. 154. 267–281. 21 indexed citations
15.
Shakil, Sadia, Chin‐Hui Lee, & Shella Keilholz. (2016). Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states. NeuroImage. 133. 111–128. 216 indexed citations
16.
Shakil, Sadia, et al.. (2016). Adaptive change point detection of dynamic functional connectivity networks. PubMed. 2016. 1135–1138. 2 indexed citations
17.
Keilholz, Shella, Jacob Billings, Kai Wang, et al.. (2016). Multiscale network activity in resting state fMRI. PubMed. 2016. 61–64. 5 indexed citations
18.
Pan, Wen‐Ju, et al.. (2015). Considerations for resting state functional MRI and functional connectivity studies in rodents. Frontiers in Neuroscience. 9. 269–269. 74 indexed citations
19.
Thompson, Garth J., Wen‐Ju Pan, Jacob Billings, et al.. (2014). Phase-amplitude coupling and infraslow (<1 Hz) frequencies in the rat brain: relationship to resting state fMRI. Frontiers in Integrative Neuroscience. 8. 41–41. 36 indexed citations
20.
Shakil, Sadia, Matthew Magnuson, Shella Keilholz, & Chin‐Hui Lee. (2014). Cluster-based analysis for characterizing dynamic functional connectivity. PubMed. 2014. 982–985. 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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