Cindy Marling

1.3k citations
26 papers · 736 · h-index 12

Impact in

Papers in

    • AI-based Problem Solving and Planning 9
    • Bayesian Modeling and Causal Inference 4
    • Machine Learning in Healthcare 3
    • Semantic Web and Ontologies 3
    • Diabetes Management and Research 10
    • Hyperglycemia and glycemic control in critically ill and hospitalized patients 4

Cindy Marling

25 papers receiving 684 citations

Peers

Cindy Marling
Comparison fields: 5 of 82
  • Health Information Management 207
  • Endocrinology, Diabetes and Metabolism 358
  • Artificial Intelligence 235
  • Health Informatics 9
  • Cardiology and Cardiovascular Medicine 88
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Citations per field
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Citations per year

Countries citing papers authored by Cindy Marling

Since Specialization
Citations

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

Fields of papers citing papers by Cindy Marling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006136
2
The OhioT1DM Dataset for Blood Glucose Level Prediction: Update 2020.
2020100
3
A Machine Learning Approach to Predicting Blood Glucose Levels for Diabetes Management
201480
4 201375
5
The OhioT1DM Dataset For Blood Glucose Level Prediction.
201872
6 201768
7 201951
8 201329
9 201223
10 201623
11 200919
12 200519
13 20219
14 20189
15 20196
16 20055
17 20023
18 20062
19 20131
20 20211

About Cindy Marling

Cindy Marling is a scholar working on Artificial Intelligence, Endocrinology, Diabetes and Metabolism, Health Information Management, Genetics and Computer Networks and Communications, having authored 26 papers that have together received 736 indexed citations. Recurring topics across this work include Diabetes Management and Research (10 papers), AI-based Problem Solving and Planning (9 papers), Artificial Intelligence in Healthcare (5 papers), Hyperglycemia and glycemic control in critically ill and hospitalized patients (4 papers), Bayesian Modeling and Causal Inference (4 papers), Machine Learning in Healthcare (3 papers), Semantic Web and Ontologies (3 papers) and Diabetes and associated disorders (2 papers). The work is most often cited by research in Health Information Management (207 citations), Endocrinology, Diabetes and Metabolism (358 citations), Artificial Intelligence (235 citations), Health Informatics (9 citations) and Cardiology and Cardiovascular Medicine (88 citations). Cindy Marling has collaborated with scholars based in United States, Norway and Italy. Frequent co-authors include Răzvan Bunescu, Isabelle Bichindaritz, Frank Schwartz, Jay H. Shubrook, Hui Shen, David Juedes, Agnar Aamodt, Stefania Montani, Peter Funk and Edwina L. Rissland. Their work appears in journals such as The Knowledge Engineering Review, AI Magazine, Expert Systems with Applications, Artificial Intelligence in Medicine and Natural Language Engineering.

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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