Adeeb Noor

1.3k citations
36 papers · 793 · h-index 12

Impact in

Papers in

Adeeb Noor

35 papers receiving 736 citations

Peers

Adeeb Noor
Comparison fields: 5 of 119
  • Health Information Management 321
  • Medical Laboratory Technology 58
  • Health Informatics 15
  • Artificial Intelligence 286
  • Computer Networks and Communications 109
Replace Jalaluddin Khan with:
Jalaluddin Khan China
Preeti Nagrath India
Salah Ud Din China
Muhammad Hammad Memon China
Javad Hassannataj Joloudari Iran
M. Kaliappan India
Ashok Ghatol India
Muhammad Nazir Pakistan
Pintu Chandra Shill Bangladesh
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Citations per year

Countries citing papers authored by Adeeb Noor

Since Specialization
Citations

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

Fields of papers citing papers by Adeeb Noor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019197
2 2019190
3 201960
4 201956
5 202441
6 202433
7 202223
8 201621
9 201918
10 202217
11 202317
12 202516
13 202211
14 202310
15 20227
16 20226
17 20246
18 20206
19 20206
20 20216

About Adeeb Noor

Adeeb Noor is a scholar working on Artificial Intelligence, Molecular Biology, Health Information Management, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 36 papers that have together received 793 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (5 papers), Machine Learning in Healthcare (5 papers), Biomedical Text Mining and Ontologies (5 papers), Imbalanced Data Classification Techniques (4 papers), Pharmacogenetics and Drug Metabolism (3 papers), Computational Drug Discovery Methods (3 papers), Probabilistic and Robust Engineering Design (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Information Management (321 citations), Medical Laboratory Technology (58 citations), Health Informatics (15 citations), Artificial Intelligence (286 citations) and Computer Networks and Communications (109 citations). Adeeb Noor has collaborated with scholars based in Saudi Arabia, Pakistan and Egypt. Frequent co-authors include Redhwan Nour, Liaqat Ali, Ashir Javeed, Shijie Zhou, Noorbakhsh Amiri Golilarz, Yongjian Liao, Javed Ali Khan, Syed Bukhari, Yakubu Imrana and Rui Wang. Their work appears in journals such as Scientific Reports, IEEE Access, Journal of the American Medical Informatics Association, PeerJ Computer Science and Sustainability.

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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