Samreen Naeem

769 total citations · 1 hit paper
26 papers, 434 citations indexed

About

Samreen Naeem is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Plant Science. According to data from OpenAlex, Samreen Naeem has authored 26 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Plant Science. Recurrent topics in Samreen Naeem's work include Spectroscopy and Chemometric Analyses (5 papers), Smart Agriculture and AI (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Samreen Naeem is often cited by papers focused on Spectroscopy and Chemometric Analyses (5 papers), Smart Agriculture and AI (5 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Samreen Naeem collaborates with scholars based in Pakistan, China and France. Samreen Naeem's co-authors include Aqib Ali, Sania Anam, Farrukh Jamal, Christophe Chesneau, Wali Khan Mashwani, M. H. Tahir, Salman Qadri, Mahmood Ul Hassan, Rehan Ahmad Khan Sherwani and Samir Brahim Belhaouari and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Sciences and Chaos An Interdisciplinary Journal of Nonlinear Science.

In The Last Decade

Samreen Naeem

23 papers receiving 408 citations

Hit Papers

An Unsupervised Machine Learning Algorithms: Comprehensiv... 2023 2026 2024 2025 2023 25 50 75
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. An Unsupervised Machine Learning Algorithms: Comprehensive Review
    2023 92 citations Samreen Naeem, Aqib Ali et al. International Journal of Computing and Digital Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samreen Naeem Pakistan 10 130 98 95 93 40 26 434
Aqib Ali Pakistan 10 132 1.0× 99 1.0× 96 1.0× 100 1.1× 40 1.0× 33 492
Sania Anam Pakistan 6 56 0.4× 44 0.4× 81 0.9× 77 0.8× 27 0.7× 19 345
Anindita Septiarini Indonesia 13 257 2.0× 153 1.6× 146 1.5× 78 0.8× 44 1.1× 92 670
Zaidah Ibrahim Malaysia 14 180 1.4× 78 0.8× 32 0.3× 96 1.0× 28 0.7× 65 596
Dalia Ezzat Egypt 6 108 0.8× 42 0.4× 141 1.5× 195 2.1× 21 0.5× 8 462
G. R. Sreekanth India 9 79 0.6× 41 0.4× 24 0.3× 47 0.5× 20 0.5× 23 245
Abdullah M. Baqasah Saudi Arabia 11 30 0.2× 22 0.2× 32 0.3× 106 1.1× 28 0.7× 36 360
Ali Kartit Morocco 11 50 0.4× 16 0.2× 59 0.6× 110 1.2× 9 0.2× 54 372
Shankar Thawkar India 14 44 0.3× 24 0.2× 218 2.3× 228 2.5× 21 0.5× 23 511
Ritesh Maurya India 11 41 0.3× 22 0.2× 52 0.5× 142 1.5× 41 1.0× 37 337

Countries citing papers authored by Samreen Naeem

Since Specialization
Citations

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

Fields of papers citing papers by Samreen Naeem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samreen Naeem

This figure shows the co-authorship network connecting the top 25 collaborators of Samreen Naeem. A scholar is included among the top collaborators of Samreen Naeem 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 Samreen Naeem. Samreen Naeem 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.
Ali, Aqib, et al.. (2023). A State of Art Survey for Big Data Processing and NoSQL Database Architecture. International Journal of Computing and Digital Systems. 14(1). 297–309. 10 indexed citations
2.
Naeem, Samreen, et al.. (2023). An Unsupervised Machine Learning Algorithms: Comprehensive Review. International Journal of Computing and Digital Systems. 13(1). 911–921. 92 indexed citations breakdown →
3.
Ali, Aqib, et al.. (2022). Machine Learning Based Classification of Lung Cancer Using CT Scan Images. 13908–13908. 2 indexed citations
4.
Ali, Aqib & Samreen Naeem. (2022). A Machine Learning Approach for The Brain Tumor Classification Using MR Imaging. 13943–13943. 2 indexed citations
5.
Naeem, Samreen, et al.. (2022). Machine Learning Methods Using Texture Feature Selection in Diagnosis of Liver Cancer. 13947–13947. 2 indexed citations
6.
Ali, Aqib, et al.. (2022). Machine Learning-Based Automated Detection of Diabetic Retinopathy Using Retinal fundus images.. 13906–13906. 2 indexed citations
7.
8.
9.
Naeem, Samreen, Aqib Ali, & Sania Anam. (2022). Computer Vision Based Skin Cancer Classification by Using Texture Features. 13933–13933. 2 indexed citations
10.
Ali, Aqib, et al.. (2022). Video Streams for The Detection of Thrown Objects from Expressways. 13932–13932. 1 indexed citations
11.
Naeem, Samreen, Aqib Ali, & Sania Anam. (2022). Analysis and Identification of Nephrolithiasis from Ultrasound Images using Machine Learning Approach. 13948–13948. 1 indexed citations
12.
Naeem, Samreen & Aqib Ali. (2022). Breast Cancer Diagnosis Using Machine Learning Techniques. 13913–13913. 4 indexed citations
13.
Ali, Aqib, et al.. (2022). Machine Learning Based Classification of Chronic Kidney Disease Using CT Scan Images. 13903–13903. 5 indexed citations
14.
Ali, Aqib, et al.. (2022). The Smart Cradle System Basis on Internet of Things. 13940–13940. 2 indexed citations
15.
Naeem, Samreen, Aqib Ali, Christophe Chesneau, et al.. (2021). The Classification of Medicinal Plant Leaves Based on Multispectral and Texture Feature Using Machine Learning Approach. Agronomy. 11(2). 263–263. 68 indexed citations
16.
Naeem, Samreen, Wali Khan Mashwani, Aqib Ali, et al.. (2021). Machine Learning-based USD/PKR Exchange Rate Forecasting Using Sentiment Analysis of Twitter Data. Computers, materials & continua/Computers, materials & continua (Print). 67(3). 3451–3461. 16 indexed citations
17.
Bantan, Rashad A. R., Aqib Ali, Samreen Naeem, et al.. (2020). Discrimination of sunflower seeds using multispectral and texture dataset in combination with region selection and supervised classification methods. Chaos An Interdisciplinary Journal of Nonlinear Science. 30(11). 113142–113142. 15 indexed citations
18.
Ali, Aqib, Salman Qadri, Wali Khan Mashwani, et al.. (2020). Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image. Entropy. 22(5). 567–567. 59 indexed citations
19.
Naeem, Samreen, Aqib Ali, Salman Qadri, et al.. (2020). Machine-Learning Based Hybrid-Feature Analysis for Liver Cancer Classification Using Fused (MR and CT) Images. Applied Sciences. 10(9). 3134–3134. 60 indexed citations
20.
Ali, Aqib, Wali Khan Mashwani, Samir Brahim Belhaouari, et al.. (2020). Machine learning approach for the classification of corn seed using hybrid features. International Journal of Food Properties. 23(1). 1110–1124. 60 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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