Md. Maniruzzaman

78 papers receiving 1.6k citations

Md. Maniruzzaman's Hit Papers

Classification and prediction of diabetes disease using machine learning paradigm 2020 · 225 citations
2250+2+4Years since publication50100150200

Peers

Md. Maniruzzaman
Comparison fields: 5 of 143
  • Health Information Management 558
  • Health Informatics 42
  • Artificial Intelligence 495
  • Complementary and alternative medicine 105
  • Nutrition and Dietetics 151
Replace Chien‐Yeh Hsu with:
Chien‐Yeh Hsu Taiwan
Hanna Suominen Finland
Md. Menhazul Abedin Bangladesh
Qi Long United States
Qing Zeng‐Treitler United States
Ole Hejlesen Denmark
Serguei Pakhomov United States
Andrea Facchinetti Italy
Nick Oliver United Kingdom
Yu Rang Park South Korea
Md. Maniruzzaman relative to Chien‐Yeh Hsu Taiwan Chien‐Yeh Hsu's profile →
Citations per field
00.5×8.8×
Chien‐Yeh Hsu · 1×
Citations per year

Countries citing papers authored by Md. Maniruzzaman

Since Specialization
Citations

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

Fields of papers citing papers by Md. Maniruzzaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Classification and prediction of diabetes disease using machine learning paradigm
Hit paper breakdown →
2020225
2 2018186
3 2017184
4 201984
5 202148
6 202443
7 202143
8 201842
9 202341
10 201935
11 202034
12 202234
13 202234
14 202032
15 201232
16 202229
17 201928
18 202227
19 202325
20 201925

About Md. Maniruzzaman

Md. Maniruzzaman is a scholar working on Cognitive Neuroscience, Cardiology and Cardiovascular Medicine, Health Information Management, Nutrition and Dietetics and Pediatrics, Perinatology and Child Health, having authored 90 papers that have together received 1.7k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (12 papers), Artificial Intelligence in Healthcare (12 papers), Child Nutrition and Water Access (11 papers), Attention Deficit Hyperactivity Disorder (8 papers), Global Maternal and Child Health (7 papers), ECG Monitoring and Analysis (6 papers), Imbalanced Data Classification Techniques (5 papers) and Bioinformatics and Genomic Networks (5 papers). The work is most often cited by research in Health Information Management (558 citations), Health Informatics (42 citations), Artificial Intelligence (495 citations), Complementary and alternative medicine (105 citations) and Nutrition and Dietetics (151 citations). Md. Maniruzzaman has collaborated with scholars based in Bangladesh, Japan and United States. Frequent co-authors include Md. Menhazul Abedin, Md. Jahanur Rahman, Benojir Ahammed, Harman S. Suri, Ayman El‐Baz, Jasjit S. Suri, Jungpil Shin, Md. Al Mehedi Hasan, Nishith Kumar and N.A.M. Faisal Ahmed. Their work appears in journals such as IEEE Access, PLoS ONE, Scientific Reports, Diabetes & Metabolic Syndrome Clinical Research & Reviews and Applied Sciences.

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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