Nahida Islam

13 papers receiving 256 citations

Peers

Nahida Islam
Comparison fields: 5 of 58
  • Pathology and Forensic Medicine 120
  • Neurology 84
  • Signal Processing 54
  • Genetics 45
  • Computer Networks and Communications 81
Replace Chengbin Hu with:
Chengbin Hu China
Kun Gao China
Asoke K. Talukder India
Zahid Nawaz India
Kazuhisa Iwamoto Japan
Chang Yun Park South Korea
Chenhao Hu China
Divya Bansal India
Nauman Javed United States
Nahida Islam relative to Chengbin Hu China Chengbin Hu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Nahida Islam

Since Specialization
Citations

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

Fields of papers citing papers by Nahida Islam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 202184
2 201481
3 201335
4 202020
5 202212
6 202011
7 20126
8 20185
9 20174
10 20123
11 20122
12
An investigation of the relationship between online activity on Studi.se and academic grades of newly arrived immigrant students : An application of educational data mining
20172
13 20132
14 20250
15
Unusual features in kala-azar: a case report.
19860

About Nahida Islam

Nahida Islam is a scholar working on Pathology and Forensic Medicine, Neurology, Artificial Intelligence, Infectious Diseases and Computer Networks and Communications, having authored 15 papers that have together received 267 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (5 papers), CNS Lymphoma Diagnosis and Treatment (3 papers), Breast Cancer Treatment Studies (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Advanced Malware Detection Techniques (2 papers), Dermatological diseases and infestations (2 papers), Network Security and Intrusion Detection (2 papers) and Nail Diseases and Treatments (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (120 citations), Neurology (84 citations), Signal Processing (54 citations), Genetics (45 citations) and Computer Networks and Communications (81 citations). Nahida Islam has collaborated with scholars based in United States, Bangladesh and South Korea. Frequent co-authors include Md. Sazzadur Rahman, Mufti Mahmud, Gihwan Cho, A. S. M. Sanwar Hosen, M. Shamim Kaiser, Ishrat Sultana, Andrew M. Evens, Ranjana H. Advani, Andrew D. Zelenetz and Izidore S. Lossos. Their work appears in journals such as Blood, Applied Sciences, British Journal of Haematology, Computers, materials & continua/Computers, materials & continua (Print) and Annals of Oncology.

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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