Deepu John

57 papers receiving 737 citations

Deepu John's Hit Papers

A predictive analytics approach for stroke prediction using machine learning and neural networks 2022 · 144 citations
1440+1+2Years since publication4080120

Peers

Deepu John
Comparison fields: 5 of 79
  • Health Information Management 107
  • Cardiology and Cardiovascular Medicine 326
  • Cognitive Neuroscience 185
  • Neurology 51
  • Biomedical Engineering 286
Replace Saroj Kumar Pandey with:
Saroj Kumar Pandey India
Ramesh Kumar Sunkaria India
Kayapanda Mandana India
Fen Miao China
Barjinder Singh Saini India
Yalçın İşler Türkiye
Yakup Kutlu Türkiye
Lina Zhao China
Chun‐Ling Lin Taiwan
Madhuri Panwar India
Deepu John relative to Saroj Kumar Pandey India Saroj Kumar Pandey's profile →
Citations per field
00.5×1.5×2.3×
Saroj Kumar Pandey · 1×
Citations per year

Countries citing papers authored by Deepu John

Since Specialization
Citations

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

Fields of papers citing papers by Deepu John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A predictive analytics approach for stroke prediction using machine learning and neural networks
Hit paper breakdown →
2022144
2 2022103
3 201666
4 202142
5 202030
6 202129
7 202228
8 202026
9 201823
10 202022
11 202118
12 202316
13 202115
14 202315
15 202014
16 202214
17 202112
18 202211
19 202410
20 202010

About Deepu John

Deepu John is a scholar working on Cardiology and Cardiovascular Medicine, Biomedical Engineering, Cognitive Neuroscience, Electrical and Electronic Engineering and Artificial Intelligence, having authored 61 papers that have together received 771 indexed citations. Recurring topics across this work include ECG Monitoring and Analysis (34 papers), EEG and Brain-Computer Interfaces (22 papers), Non-Invasive Vital Sign Monitoring (19 papers), Analog and Mixed-Signal Circuit Design (11 papers), Anomaly Detection Techniques and Applications (4 papers), Advanced Memory and Neural Computing (4 papers), Advanced Neural Network Applications (4 papers) and Hemodynamic Monitoring and Therapy (3 papers). The work is most often cited by research in Health Information Management (107 citations), Cardiology and Cardiovascular Medicine (326 citations), Cognitive Neuroscience (185 citations), Neurology (51 citations) and Biomedical Engineering (286 citations). Deepu John has collaborated with scholars based in Ireland, Singapore and United States. Frequent co-authors include Barry Cardiff, Soumyabrata Dev, Chun-Huat Heng, Yong Lian, Bharadwaj Veeravalli, Hewei Wang, Rajesh C. Panicker, Xiaoyang Zhang, Avishek Nag and Yongfu Li. Their work appears in journals such as IEEE Transactions on Biomedical Circuits and Systems, IEEE Access, IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Sensors Journal and IEEE Internet of Things Journal.

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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