Lasith Adhikari

20 papers receiving 292 citations

Peers

Lasith Adhikari
Comparison fields: 5 of 75
  • Health Informatics 18
  • Nephrology 36
  • Critical Care and Intensive Care Medicine 18
  • Family Practice 5
  • Emergency Medicine 22
Replace Christopher E. Gillies with:
Christopher E. Gillies United States
Nianzong Hou China
Kuo-Ching Yuan Taiwan
Swapna Abhyankar United States
Patrick Botting United States
Hazra S. Moeniralam Netherlands
Dongkai Li China
Eiichiro Uchino Japan
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Citations per field
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Citations per year

Countries citing papers authored by Lasith Adhikari

Since Specialization
Citations

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

Fields of papers citing papers by Lasith Adhikari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021131
2 201958
3 201725
4 201612
5 201610
6 20229
7 20169
8 20209
9 20176
10 20156
11 20224
12 20174
13 20174
14 20173
15 20162
16
Trust-region methods for nonconvex sparse recovery optimization
20161
17 20171
18
Nonconvex Sparse Recovery Methods
20171
19 20161
20 20161

About Lasith Adhikari

Lasith Adhikari is a scholar working on Biomedical Engineering, Molecular Biology, Computational Mechanics, Radiology, Nuclear Medicine and Imaging and Genetics, having authored 22 papers that have together received 297 indexed citations. Recurring topics across this work include Photoacoustic and Ultrasonic Imaging (9 papers), Sparse and Compressive Sensing Techniques (7 papers), Genomic variations and chromosomal abnormalities (6 papers), Optical Imaging and Spectroscopy Techniques (6 papers), Genomics and Phylogenetic Studies (5 papers), Genomics and Rare Diseases (4 papers), Sepsis Diagnosis and Treatment (4 papers) and Hemodynamic Monitoring and Therapy (2 papers). The work is most often cited by research in Health Informatics (18 citations), Nephrology (36 citations), Critical Care and Intensive Care Medicine (18 citations), Family Practice (5 citations) and Emergency Medicine (22 citations). Lasith Adhikari has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Roummel F. Marcia, R. W. M. A. Madushani, Suzanne Sindi, Han Kim, Eduardo Mireles‐Cabodevila, Mary E. Lough, Leo Anthony Celi, Marie‐Laure Charpignon, An-Kwok Ian Wong and Azade Tabaie. Their work appears in journals such as Journal of Critical Care, JAMA Network Open, Journal of Surgical Research, IEEE Access and PLoS ONE.

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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