Sofia Pillai

1.1k citations
20 papers · 761 · 1 hit paper · h-index 11

Impact in

Papers in

Sofia Pillai

19 papers receiving 709 citations

Sofia Pillai's Hit Papers

COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm 2020 · 368 citations
3680+2+4Years since publication100200300

Peers

Sofia Pillai
Comparison fields: 5 of 124
  • Health Information Management 89
  • Health Informatics 27
  • Modeling and Simulation 66
  • Signal Processing 143
  • Radiology, Nuclear Medicine and Imaging 208
Replace Michał Wieczorek with:
Michał Wieczorek Poland
Jakub Siłka Poland
Jianji Wang China
Ibrahim Gad Egypt
Daniel Jarrett United Kingdom
Ramon Gomes da Silva Brazil
Farah Shahid Pakistan
Nikola Anđelić Croatia
Hongping Hu China
Prithwish Chakraborty United States
Sofia Pillai relative to Michał Wieczorek Poland Michał Wieczorek's profile →
Citations per field
00.5×11×
Michał Wieczorek · 1×
Citations per year

Countries citing papers authored by Sofia Pillai

Since Specialization
Citations

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

Fields of papers citing papers by Sofia Pillai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Sofia Pillai, 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 Sofia Pillai Line = papers co-authored together Sofia Pillai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
COVID-19 Patient Health Prediction Using Boosted Random Forest Algorithm
Hit paper breakdown →
2020368
2 198781
3 200563
4
Reinforced concrete design
198850
5 202048
6 202235
7 202027
8 202022
9 202315
10 202012
11 202010
12 20199
13 20207
14 20216
15
SUPER RESOLUTION MASK RCNN BASED TRANSFER DEEP LEARNING APPROACH FOR IDENTIFICATION OF BIRD SPECIES
20212
16 20232
17 20192
18 20251
19 20221
20 20190

About Sofia Pillai

Sofia Pillai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Signal Processing and Radiology, Nuclear Medicine and Imaging, having authored 20 papers that have together received 761 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (3 papers), Identification and Quantification in Food (3 papers), Digital Imaging for Blood Diseases (2 papers), Direction-of-Arrival Estimation Techniques (2 papers), Face and Expression Recognition (2 papers), Artificial Intelligence in Healthcare (2 papers), IoT and Edge/Fog Computing (2 papers) and Remote-Sensing Image Classification (2 papers). The work is most often cited by research in Health Information Management (89 citations), Health Informatics (27 citations), Modeling and Simulation (66 citations), Signal Processing (143 citations) and Radiology, Nuclear Medicine and Imaging (208 citations). Sofia Pillai has collaborated with scholars based in India, United States and Nepal. Frequent co-authors include F. Haber, Ali Kashif Bashir, Celestine Iwendi, Ohyun Jo, Jyotir Moy Chatterjee, Y. Bar-Ness, R. Lakshmana Kumar, Fadi Al‐Turjman, M. M. Raghuwanshi and Osamah Ibrahim Khalaf. Their work appears in journals such as Frontiers in Public Health, IEEE Sensors Journal, Intelligent Automation & Soft Computing, Studies in big data and Lecture notes in networks and systems.

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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