Hanane Allioui

16 papers receiving 397 citations

Hanane Allioui's Hit Papers

Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey 2023 · 268 citations
2680+1+2Years since publication50100150200250

Peers

Hanane Allioui
Comparison fields: 5 of 94
  • Health Informatics 10
  • Neurology 45
  • Management Information Systems 50
  • Information Systems 68
  • Radiology, Nuclear Medicine and Imaging 60
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Countries citing papers authored by Hanane Allioui

Since Specialization
Citations

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

Fields of papers citing papers by Hanane Allioui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Hanane Allioui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hanane Allioui Line = papers co-authored together Hanane Allioui links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1
Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey
Hit paper breakdown →
2023268
2 202262
3 201932
4 202014
5 202114
6 20227
7 20167
8 20246
9 20196
10 20225
11 20203
12 20203
13
An Improved Image Segmentation System: A Cooperative Multi-agent Strategy for 2D/3D Medical Images
20202
14 20241
15 20201
16 20231
17 20250

About Hanane Allioui

Hanane Allioui is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Economics and Econometrics, Computer Networks and Communications and Neurology, having authored 17 papers that have together received 432 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (3 papers), Brain Tumor Detection and Classification (3 papers), Mathematical Biology Tumor Growth (2 papers), COVID-19 Pandemic Impacts (2 papers), COVID-19 diagnosis using AI (2 papers), Digital Imaging for Blood Diseases (1 paper), Blockchain Technology Applications and Security (1 paper) and Entrepreneurship Studies and Influences (1 paper). The work is most often cited by research in Health Informatics (10 citations), Neurology (45 citations), Management Information Systems (50 citations), Information Systems (68 citations) and Radiology, Nuclear Medicine and Imaging (60 citations). Hanane Allioui has collaborated with scholars based in Morocco, Spain and Lithuania. Frequent co-authors include Youssef Mourdi, Mohamed Sadgal, Mazin Abed Mohammed, Belal Al‐Khateeb, Karrar Hameed Abdulkareem, Begonya García-Zapirain, Robertas Damaševičius, Abdelaziz El Fazziki and Rytis Maskeliūnas. Their work appears in journals such as Journal of Personalized Medicine, Evolutionary Intelligence, Multimedia Tools and Applications, Machine Vision and Applications and Journal of Ambient Intelligence and Humanized Computing.

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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