Ibrahem Kandel

1.0k total citations · 1 hit paper
9 papers, 710 citations indexed

About

Ibrahem Kandel is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Ibrahem Kandel has authored 9 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Artificial Intelligence. Recurrent topics in Ibrahem Kandel's work include Digital Imaging for Blood Diseases (5 papers), AI in cancer detection (5 papers) and COVID-19 diagnosis using AI (4 papers). Ibrahem Kandel is often cited by papers focused on Digital Imaging for Blood Diseases (5 papers), AI in cancer detection (5 papers) and COVID-19 diagnosis using AI (4 papers). Ibrahem Kandel collaborates with scholars based in Portugal, Slovenia and Italy. Ibrahem Kandel's co-authors include Mauro Castelli, Aleš Popovič and Luca Manzoni and has published in prestigious journals such as Applied Sciences, ICT Express and Emerging Science Journal.

In The Last Decade

Ibrahem Kandel

9 papers receiving 686 citations

Hit Papers

align trajectories

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.

The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset

2020 363 citations Ibrahem Kandel, Mauro Castelli ICT Express profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ibrahem Kandel Portugal	9	216	204	201	79	48	9	710
Aamir Shahzad Pakistan	16	148 0.7×	121 0.6×	167 0.8×	134 1.7×	72 1.5×	47	681
Raul Victor M. da Nóbrega Brazil	9	248 1.1×	249 1.2×	184 0.9×	76 1.0×	39 0.8×	9	812
Yanbei Liu China	14	143 0.7×	203 1.0×	216 1.1×	36 0.5×	48 1.0×	54	648
Chirag Patel India	11	120 0.6×	255 1.3×	370 1.8×	74 0.9×	45 0.9×	37	961
Bayram Akdemïr Türkiye	14	131 0.6×	202 1.0×	213 1.1×	39 0.5×	38 0.8×	43	621
Xiaoming Qi China	11	150 0.7×	157 0.8×	268 1.3×	45 0.6×	21 0.4×	33	736
Ganbayar Batchuluun South Korea	17	192 0.9×	204 1.0×	363 1.8×	105 1.3×	64 1.3×	34	777
Zifan Wang United States	9	145 0.7×	449 2.2×	331 1.6×	46 0.6×	33 0.7×	18	912
Yambem Jina Chanu India	8	155 0.7×	262 1.3×	438 2.2×	71 0.9×	67 1.4×	21	1.0k

Countries citing papers authored by Ibrahem Kandel

Since Specialization

Citations

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

Fields of papers citing papers by Ibrahem Kandel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ibrahem Kandel

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

All Works

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9 of 9 papers shown

1.

Kandel, Ibrahem, Mauro Castelli, & Luca Manzoni. (2022). Brightness as an Augmentation Technique for Image Classification. Emerging Science Journal. 6(4). 881–892. 38 indexed citations

2.

Kandel, Ibrahem & Mauro Castelli. (2021). Improving convolutional neural networks performance for image classification using test time augmentation: a case study using MURA dataset. Health Information Science and Systems. 9(1). 33–33. 17 indexed citations

3.

Kandel, Ibrahem, Mauro Castelli, & Aleš Popovič. (2021). Comparing Stacking Ensemble Techniques to Improve Musculoskeletal Fracture Image Classification. Journal of Imaging. 7(6). 100–100. 29 indexed citations

4.

Kandel, Ibrahem & Mauro Castelli. (2020). Transfer Learning with Convolutional Neural Networks for Diabetic Retinopathy Image Classification. A Review. Applied Sciences. 10(6). 2021–2021. 115 indexed citations

5.

Kandel, Ibrahem, Mauro Castelli, & Aleš Popovič. (2020). Comparative Study of First Order Optimizers for Image Classification Using Convolutional Neural Networks on Histopathology Images. Journal of Imaging. 6(9). 92–92. 51 indexed citations

6.

Kandel, Ibrahem & Mauro Castelli. (2020). How Deeply to Fine-Tune a Convolutional Neural Network: A Case Study Using a Histopathology Dataset. Applied Sciences. 10(10). 3359–3359. 58 indexed citations

7.

Kandel, Ibrahem & Mauro Castelli. (2020). A Novel Architecture to Classify Histopathology Images Using Convolutional Neural Networks. Applied Sciences. 10(8). 2929–2929. 14 indexed citations

8.

Kandel, Ibrahem & Mauro Castelli. (2020). The effect of batch size on the generalizability of the convolutional neural networks on a histopathology dataset. ICT Express. 6(4). 312–315. 363 indexed citations breakdown →

9.

Kandel, Ibrahem, Mauro Castelli, & Aleš Popovič. (2020). Musculoskeletal Images Classification for Detection of Fractures Using Transfer Learning. Journal of Imaging. 6(11). 127–127. 25 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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