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.
A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning
2019432 citationsArshia Rehman, Saeeda Naz et al.Circuits Systems and Signal Processingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Faiza Akram'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 Faiza Akram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faiza Akram more than expected).
This network shows the impact of papers produced by Faiza Akram. 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 Faiza Akram. The network helps show where Faiza Akram may publish in the future.
Co-authorship network of co-authors of Faiza Akram
This figure shows the co-authorship network connecting the top 25 collaborators of Faiza Akram.
A scholar is included among the top collaborators of Faiza Akram 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 Faiza Akram. Faiza Akram is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Akram, Faiza, et al.. (2022). Use Of Radiological Diagnostic Modalities In Tertiary Care Hospital - How Do The Clinicians Decide About Type Of Modality And Clinician Perception Regarding Hazards Associated With Radiological Imaging Modalities?. PubMed. 33(Suppl 1)(4). S788–S790.
8.
Akram, Faiza, et al.. (2020). Validity Of Transabdominal Ultrasound Scan In The Prediction Of Uterine Scar Thickness.. PubMed. 32(1). 68–72.5 indexed citations
9.
Rehman, Arshia, Saeeda Naz, Imran Razzak, Faiza Akram, & Muhammad Imran. (2019). A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning. Circuits Systems and Signal Processing. 39(2). 757–775.432 indexed citations breakdown →
10.
Akram, Faiza, et al.. (2019). Paediatrics Brain Imaging In Epilepsy: Common Presenting Symptoms And Spectrum Of Abnormalities Detected On MRI.. PubMed. 29(2). 215–218.2 indexed citations
11.
Akram, Faiza, et al.. (2019). Non-Contrast Enhanced Multi-Slice Ct-Kub In Renal Colic: Spectrum Of Abnormalities Detected On Ct Kub And Assessment Of Referral Patterns.. PubMed. 31(3). 415–417.3 indexed citations
12.
Akram, Faiza, et al.. (2019). Obesity And Diabetes As Determinants Of Vitamin D Deficiency.. PubMed. 31(3). 432–435.10 indexed citations
13.
Ara, Iffat, et al.. (2015). Comparison of perinatal outcome of growth restricted fetuses with normal and abnormal umbilical artery Doppler waveforms.. PubMed. 26(3). 344–8.7 indexed citations
Akram, Faiza, et al.. (2014). A Comparative Study to Know the Causes of Spelling Errors Committed by Learners of English at Elementary Level in Distract Kasur and Lahore in Pakistan.6 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.