D.L. Hudson

766 citations
60 papers · 524 · h-index 10

Impact in

Papers in

    • Neural Networks and Applications 17
    • Fuzzy Logic and Control Systems 9
    • Cognitive Science and Mapping 6
    • AI-based Problem Solving and Planning 5
    • Statistical and Computational Modeling 4
    • Artificial Intelligence and Decision Support Systems 19

D.L. Hudson

52 papers receiving 471 citations

Peers

D.L. Hudson
Comparison fields: 5 of 95
  • Cardiology and Cardiovascular Medicine 152
  • Health Information Management 24
  • Signal Processing 60
  • Artificial Intelligence 179
  • Information Systems 102
Replace Donna L. Hudson with:
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Citations per field
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Citations per year

Countries citing papers authored by D.L. Hudson

Since Specialization
Citations

This map shows the geographic impact of D.L. Hudson'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. Hudson 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. Hudson more than expected).

Fields of papers citing papers by D.L. Hudson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside D.L. Hudson, 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. Hudson Line = papers co-authored together D.L. Hudson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996145
2 199452
3 198840
4 199534
5 199122
6 198822
7 200321
8 200219
9 198813
10
Determination of Testing Efficacy in Carcinoma of the Lung Using a Neural Network Model.
198810
11 19859
12 20059
13 20039
14 20029
15 20028
16 20027
17 20027
18 20037
19 19976
20 20036

About D.L. Hudson

D.L. Hudson is a scholar working on Artificial Intelligence, Information Systems, Cardiology and Cardiovascular Medicine, Molecular Biology and Statistical and Nonlinear Physics, having authored 60 papers that have together received 524 indexed citations. Recurring topics across this work include Artificial Intelligence and Decision Support Systems (19 papers), Neural Networks and Applications (17 papers), Fuzzy Logic and Control Systems (9 papers), Heart Rate Variability and Autonomic Control (8 papers), Cognitive Science and Mapping (6 papers), AI-based Problem Solving and Planning (5 papers), Chaos control and synchronization (4 papers) and Statistical and Computational Modeling (4 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (152 citations), Health Information Management (24 citations), Signal Processing (60 citations), Artificial Intelligence (179 citations) and Information Systems (102 citations). D.L. Hudson has collaborated with scholars based in United States and Argentina. Frequent co-authors include Madeline Cohen, Prakash Deedwania, P. B. Raven, Melvyn Smith, Marie L. Smith, Oscar U. Scremin, Paul H. Guth, Mark Kramer, Andrew J. Szeri and Mark A. Kramer. Their work appears in journals such as International Journal of Intelligent Systems, Journal of Applied Physiology, Methods of Information in Medicine, International Journal of Medical Informatics and Journal of the American College of Cardiology.

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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