Jaber Alyami

610 total citations
38 papers, 390 citations indexed

About

Jaber Alyami is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Neurology. According to data from OpenAlex, Jaber Alyami has authored 38 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Artificial Intelligence and 10 papers in Neurology. Recurrent topics in Jaber Alyami's work include Brain Tumor Detection and Classification (9 papers), AI in cancer detection (8 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Jaber Alyami is often cited by papers focused on Brain Tumor Detection and Classification (9 papers), AI in cancer detection (8 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Jaber Alyami collaborates with scholars based in Saudi Arabia, United Kingdom and Pakistan. Jaber Alyami's co-authors include Mahmoud Ragab, Romany F. Mansour, Ashwag Albukhari, Amjad Rehman, Luca Marciani, Saeed Ali Bahaj, Robert E. Spiller, Tanzila Saba, Sudipta Roy and Penny Gowland and has published in prestigious journals such as Scientific Reports, IEEE Access and Nutrients.

In The Last Decade

Jaber Alyami

36 papers receiving 380 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaber Alyami Saudi Arabia 11 161 160 86 61 37 38 390
Tingwei Wang China 15 100 0.6× 40 0.3× 34 0.4× 49 0.8× 18 0.5× 59 531
Yu Guan China 11 238 1.5× 36 0.2× 18 0.2× 106 1.7× 9 0.2× 49 524
Shadab Khan United States 11 152 0.9× 60 0.4× 16 0.2× 42 0.7× 48 1.3× 24 489
Zahra Jafari Iran 8 40 0.2× 45 0.3× 19 0.2× 13 0.2× 20 0.5× 41 244
Mingyu Kim South Korea 7 184 1.1× 103 0.6× 17 0.2× 53 0.9× 4 0.1× 14 372
Chun Cai China 5 267 1.7× 80 0.5× 44 0.5× 106 1.7× 3 0.1× 10 555
Sofia Zahia Spain 8 127 0.8× 170 1.1× 42 0.5× 81 1.3× 12 406
Xiaoxue Long China 5 226 1.4× 51 0.3× 30 0.3× 96 1.6× 4 0.1× 9 559

Countries citing papers authored by Jaber Alyami

Since Specialization
Citations

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

Fields of papers citing papers by Jaber Alyami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaber Alyami

This figure shows the co-authorship network connecting the top 25 collaborators of Jaber Alyami. A scholar is included among the top collaborators of Jaber Alyami 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 Jaber Alyami. Jaber Alyami 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.
Alyami, Jaber, et al.. (2024). Point shear wave elastography application in assessment pancreas tissue stiffness: A pilot study. Radiography. 31(1). 328–332. 1 indexed citations
2.
Alyami, Hamad S., et al.. (2024). Comprehensive Review of Radiological Applications in Cancer Detection and Monitoring. Journal of Ecohumanism. 3(8). 1 indexed citations
3.
4.
Camps, Guido, Luca Marciani, Robert E. Spiller, et al.. (2024). Intra‐ and interindividual variability in fasted gastric content volume. Neurogastroenterology & Motility. 36(11). e14904–e14904. 2 indexed citations
5.
Ragab, Mahmoud, et al.. (2024). Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images. Scientific Reports. 14(1). 29448–29448. 3 indexed citations
6.
Al‐Otaibi, Shaha, Muhammad Mujahid, Amjad Rehman, et al.. (2024). Dual Attention Convolutional AutoEncoder for Diagnosis of Alzheimer’s Disorder in Patients Using Neuroimaging and MRI Features. IEEE Access. 12. 58722–58739. 8 indexed citations
7.
Alyami, Jaber, et al.. (2024). Feasibility of Point Shear Wave Elastography for Evaluating Renal CorticalThickness: A Prospective Study. Current Medical Imaging Formerly Current Medical Imaging Reviews. 20. e15734056280317–e15734056280317. 1 indexed citations
8.
Alyami, Jaber, et al.. (2023). Annual radiation dose monitoring for catheterization laboratory operators. Radiation Physics and Chemistry. 216. 111431–111431. 1 indexed citations
9.
Alyami, Jaber, Susan E. Pritchard, Robert E. Spiller, et al.. (2023). In vivo observation of a stomach road or ‘Magenstrasse’ for gastric emptying using MRI imaging in healthy humans. Clinical Nutrition Open Science. 51. 35–43. 2 indexed citations
10.
Alyami, Jaber, et al.. (2023). Tumor Localization and Classification from MRI of Brain using Deep Convolution Neural Network and Salp Swarm Algorithm. Cognitive Computation. 16(4). 2036–2046. 36 indexed citations
11.
Ragab, Mahmoud & Jaber Alyami. (2022). Stacked Gated Recurrent Unit Classifier with CT Images for Liver Cancer Classification. Computer Systems Science and Engineering. 44(3). 2309–2322. 5 indexed citations
12.
Alyami, Jaber, et al.. (2022). Automatic skin lesions detection from images through microscopic hybrid features set and machine learning classifiers. Microscopy Research and Technique. 85(11). 3600–3607. 10 indexed citations
13.
Ragab, Mahmoud, Samah Alshehri, Hibah M. Aldawsari, et al.. (2022). COVID-19 Identification System Using Transfer Learning Technique With Mobile-NetV2 and Chest X-Ray Images. Frontiers in Public Health. 10. 819156–819156. 5 indexed citations
14.
Alyami, Jaber, et al.. (2022). Investigating Confidence Levels of Saudi Clinical Supervisors in Radiology Departments. Advances in Medical Education and Practice. Volume 13. 797–808. 1 indexed citations
15.
Shubayr, Nasser, et al.. (2022). Radiographers' awareness level of MRI-induced vertigo and their perspectives on the post-examination care provided to patients in Saudi Arabia. Journal of medical imaging and radiation sciences. 53(4). 633–639. 3 indexed citations
16.
Alsharif, Walaa, et al.. (2022). The Motivational Factors of Choosing Diagnostic Radiology as a Profession Among Saudi Radiography Students. Advances in Medical Education and Practice. Volume 13. 955–967. 4 indexed citations
17.
Ragab, Mahmoud, Samah Alshehri, Nabil A. Alhakamy, et al.. (2022). Machine Learning with Quantum Seagull Optimization Model for COVID-19 Chest X-Ray Image Classification. Journal of Healthcare Engineering. 2022. 1–13. 13 indexed citations
18.
Williams, Hannah, Konstantinos Argyriou, David Gunn, et al.. (2021). Test–retest assessment of non-contrast MRI sequences to characterise and quantify the small bowel wall in healthy participants. Magnetic Resonance Materials in Physics Biology and Medicine. 34(6). 791–804. 4 indexed citations
19.
Alyami, Jaber, Gleb E. Yakubov, Susan E. Pritchard, et al.. (2019). Glycaemic, gastrointestinal, hormonal and appetitive responses to pearl millet or oats porridge breakfasts: a randomised, crossover trial in healthy humans. British Journal Of Nutrition. 122(10). 1142–1154. 25 indexed citations
20.
Alyami, Jaber, Susan E. Pritchard, Caroline L. Hoad, et al.. (2017). Glycaemic, gastrointestinal and appetite responses to breakfast porridges from ancient cereal grains: A MRI pilot study in healthy humans. Food Research International. 118. 49–57. 22 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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