Abdullahi Umar Ibrahim

29 papers receiving 553 citations

Abdullahi Umar Ibrahim's Hit Papers

Pneumonia Classification Using Deep Learning from Chest X-ray Images During COVID-19 2021 · 241 citations
2410+1+3Years since publication50100150200

Peers

Abdullahi Umar Ibrahim
Comparison fields: 5 of 102
  • Health Informatics 30
  • Radiology, Nuclear Medicine and Imaging 266
  • Business and International Management 16
  • Artificial Intelligence 164
  • Infectious Diseases 63
Replace Md. Abdul Based with:
Md. Abdul Based Bangladesh
Cong Fang China
Ruhan Liu China
Mubarak Taiwo Mustapha Cyprus
Liming Wang China
Abolfazl Zargari Khuzani United States
Mohammad Asadur Rahman Bangladesh
Noorul Wahab Egypt
Junghwan Cho South Korea
Zubaida Said Ameen Cyprus
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Countries citing papers authored by Abdullahi Umar Ibrahim

Since Specialization
Citations

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

Fields of papers citing papers by Abdullahi Umar Ibrahim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Abdullahi Umar Ibrahim. 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 Abdullahi Umar Ibrahim. The network helps show where Abdullahi Umar Ibrahim may publish in the future.

Co-authors

The 25 scholars most cited alongside Abdullahi Umar Ibrahim, 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 Abdullahi Umar Ibrahim Line = papers co-authored together Abdullahi Umar Ibrahim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Pneumonia Classification Using Deep Learning from Chest X-ray Images During COVID-19
Hit paper breakdown →
2021241
2 202356
3 202041
4 202323
5 202321
6 202119
7 202219
8 202419
9 202419
10 202219
11 202116
12 202413
13 202112
14 202411
15 202211
16 20239
17 20246
18 20235
19
Genome Engineering Using the CRISPR Cas9 System
20195
20 20243

About Abdullahi Umar Ibrahim

Abdullahi Umar Ibrahim is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Infectious Diseases and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 583 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (9 papers), Advanced biosensing and bioanalysis techniques (8 papers), CRISPR and Genetic Engineering (6 papers), Biosensors and Analytical Detection (6 papers), SARS-CoV-2 detection and testing (4 papers), Image Processing Techniques and Applications (3 papers), AI in cancer detection (3 papers) and Digital Imaging for Blood Diseases (3 papers). The work is most often cited by research in Health Informatics (30 citations), Radiology, Nuclear Medicine and Imaging (266 citations), Business and International Management (16 citations), Artificial Intelligence (164 citations) and Infectious Diseases (63 citations). Abdullahi Umar Ibrahim has collaborated with scholars based in Cyprus, Indonesia and Türkiye. Frequent co-authors include Mehmet Özsöz, Fadi Al‐Turjman, Sertan Serte, Polycarp Shizawaliyi Yakoi, Yeni Wahyuni Hartati, Irkham Irkham, Fadi Al‐Turjman, Zubaida Said Ameen, Ari Hardianto and Mohammed Awad Abuhussain. Their work appears in journals such as Sensing and Bio-Sensing Research, Sensors, Clinica Chimica Acta, International Journal of Food Science & Technology and Fractals.

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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