T Jayalakshmi

725 total citations
15 papers, 401 citations indexed

About

T Jayalakshmi is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence and Surgery. According to data from OpenAlex, T Jayalakshmi has authored 15 papers receiving a total of 401 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Pulmonary and Respiratory Medicine, 3 papers in Artificial Intelligence and 2 papers in Surgery. Recurrent topics in T Jayalakshmi's work include Artificial Intelligence in Healthcare (2 papers), Neural Networks and Applications (2 papers) and Traditional Chinese Medicine Studies (2 papers). T Jayalakshmi is often cited by papers focused on Artificial Intelligence in Healthcare (2 papers), Neural Networks and Applications (2 papers) and Traditional Chinese Medicine Studies (2 papers). T Jayalakshmi collaborates with scholars based in India and United States. T Jayalakshmi's co-authors include A. Santhakumaran, G. P. Dureja, A Toby Prevost, N K Bhide, H. L. Kaul, Akanksha Das, Abhay Uppe, Girija Nair, Parmod K. Bithal and Adele Balram and has published in prestigious journals such as The Lancet, SHILAP Revista de lepidopterología and Anesthesia & Analgesia.

In The Last Decade

T Jayalakshmi

13 papers receiving 369 citations

Peers

T Jayalakshmi
Comparison fields: 5 of 121
  • Artificial Intelligence 108
  • Health Information Management 80
  • Information Systems 46
  • Anesthesiology and Pain Medicine 45
  • Physiology 42
Replace Simone Del Favero with:
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Citations per field, relative to T Jayalakshmi
T Jayalakshmi · 1×
Citations per year, relative to T Jayalakshmi
T Jayalakshmi · 1×

Countries citing papers authored by T Jayalakshmi

Since Specialization
Citations

This map shows the geographic impact of T Jayalakshmi'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 T Jayalakshmi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T Jayalakshmi more than expected).

Fields of papers citing papers by T Jayalakshmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T Jayalakshmi

This figure shows the co-authorship network connecting the top 25 collaborators of T Jayalakshmi. A scholar is included among the top collaborators of T Jayalakshmi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with T Jayalakshmi. T Jayalakshmi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
# Work Indexed citations
1 1
2 0
3 3
4 224
5 70
6
Improved Gradient Descent Back Propagation Neural Networks for Diagnoses of Type II Diabetes Mellitus
4
7
Diagnose The Type II Diabetes Using Feed Forward Back Propagation Neural Networks
1
8 52
9 2
10 9
11
Potassium homeostasis during & after cardiopulmonary bypass.
2
12 4
13 2
14 24
15 3

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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2026