D.L. Bisset

616 citations
35 papers · 360 · h-index 10

Impact in

Papers in

    • Neural Networks and Applications 20
    • Neural Networks and Reservoir Computing 6
    • Fuzzy Logic and Control Systems 5
    • Machine Learning and ELM 3

D.L. Bisset

30 papers receiving 336 citations

Peers

D.L. Bisset
Comparison fields: 5 of 80
  • Dermatology 53
  • Artificial Intelligence 93
  • Oral Surgery 19
  • Rheumatology 39
  • Epidemiology 82
Replace Elizabeth Guevara‐Gutiérrez with:
Elizabeth Guevara‐Gutiérrez Mexico
Steven M. Montner United States
Kenji Hoshi Japan
Chenhao Hu China
Dániel Tóth United Kingdom
Adam R. Sweeney United States
Neil Joshi United States
Jyoti Kini India
Joo‐Hoo Park South Korea
E Martin United States
D.L. Bisset relative to Elizabeth Guevara‐Gutiérrez Mexico Elizabeth Guevara‐Gutiérrez's profile →
Citations per field
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Elizabeth Guevara‐Gutiérrez · 1×
Citations per year

Countries citing papers authored by D.L. Bisset

Since Specialization
Citations

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

Fields of papers citing papers by D.L. Bisset

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.L. Bisset. 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 D.L. Bisset. The network helps show where D.L. Bisset may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200268
2 200242
3 199528
4 198826
5 198826
6 199525
7 199424
8 200118
9 199117
10 199517
11 19928
12 19937
13 19947
14 20065
15 19925
16 19955
17 19945
18 19924
19
A comparative study of neural network structures for practical application in a pattern recognition environment
19893
20 20023

About D.L. Bisset

D.L. Bisset is a scholar working on Artificial Intelligence, Surgery, Pathology and Forensic Medicine, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 35 papers that have together received 360 indexed citations. Recurring topics across this work include Neural Networks and Applications (20 papers), Neural Networks and Reservoir Computing (6 papers), Fuzzy Logic and Control Systems (5 papers), Machine Learning and ELM (3 papers), Advanced Memory and Neural Computing (3 papers), Lymphoma Diagnosis and Treatment (2 papers), Neural dynamics and brain function (2 papers) and Soft tissue tumor case studies (1 paper). The work is most often cited by research in Dermatology (53 citations), Artificial Intelligence (93 citations), Oral Surgery (19 citations), Rheumatology (39 citations) and Epidemiology (82 citations). D.L. Bisset has collaborated with scholars based in United Kingdom, Germany and India. Frequent co-authors include M.C. Fairhurst, Justin Pearson, Germano C. Vasconcelos, Richard Prescott, L J McWilliam, Stewart Watson, Peter Davenport, C. James Kirkpatrick, Alan Curry and J.A. Morris. Their work appears in journals such as Histopathology, Pattern Recognition Letters, Journal of Clinical Pathology, Electronics Letters and Neural Computing and Applications.

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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