Deep Bera

440 citations
24 papers · 354 · h-index 8

Impact in

Papers in

Deep Bera

24 papers receiving 341 citations

Peers

Deep Bera
Comparison fields: 5 of 51
  • Radiology, Nuclear Medicine and Imaging 173
  • Biomedical Engineering 222
  • Mechanics of Materials 74
  • Cardiology and Cardiovascular Medicine 47
  • Electrical and Electronic Engineering 95
Replace Coşkun Tekeş with:
Coşkun Tekeş United States
Iwaki Akiyama Japan
Abdollah Saberi Iran
Gokce Gurun United States
Haobo Zhang China
Guillaume Férin France
Christian Prins Netherlands
Hong Ding China
Edite Figueiras Portugal
P.S. Ruggera United States
Deep Bera relative to Coşkun Tekeş United States Coşkun Tekeş's profile →
Citations per field
00.5×1.5×2.4×
Coşkun Tekeş · 1×
Citations per year

Countries citing papers authored by Deep Bera

Since Specialization
Citations

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

Fields of papers citing papers by Deep Bera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201687
2 201782
3 201854
4 201136
5 201817
6 201810
7
Mortality risk assessment for ICU patients using logistic regression
20129
8 20187
9 20166
10 20156
11 20185
12 20165
13 20145
14 20115
15 20224
16 20104
17 20093
18 20192
19 20172
20 20111

About Deep Bera

Deep Bera is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Mechanics of Materials, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 354 indexed citations. Recurring topics across this work include Ultrasound Imaging and Elastography (14 papers), Ultrasonics and Acoustic Wave Propagation (9 papers), Microwave Imaging and Scattering Analysis (5 papers), Advanced MRI Techniques and Applications (5 papers), Electrical and Bioimpedance Tomography (4 papers), Advanced Image Processing Techniques (4 papers), Image and Signal Denoising Methods (4 papers) and Analog and Mixed-Signal Circuit Design (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (173 citations), Biomedical Engineering (222 citations), Mechanics of Materials (74 citations), Cardiology and Cardiovascular Medicine (47 citations) and Electrical and Electronic Engineering (95 citations). Deep Bera has collaborated with scholars based in Netherlands and India. Frequent co-authors include Nico de Jong, Johan G. Bosch, Martin D. Verweij, Hendrik J. Vos, Michiel A. P. Pertijs, Emile Noothout, Zhao Chen, Zu‐Yao Chang, Chao Chen and Ajit Bopardikar. Their work appears in journals such as Ultrasound in Medicine & Biology, Physics in Medicine and Biology, IEEE Journal of Solid-State Circuits, Journal of Controlled Release and IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control.

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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