Carl Sable

553 citations
13 papers · 436 · h-index 9

Impact in

Papers in

Carl Sable

13 papers receiving 385 citations

Peers

Carl Sable
Comparison fields: 5 of 52
  • Artificial Intelligence 294
  • Computer Vision and Pattern Recognition 138
  • Information Systems 115
  • Signal Processing 38
  • Health Informatics 2
Replace Tianlei Hu with:
Tianlei Hu China
Hwee-Boon Low Singapore
Fumiyo Fukumoto Japan
Siddharth Gopal United States
Myung-Gil Jang South Korea
Lobna Hlaoua Tunisia
Atulya Velivelli United States
Hiroyuki Shinnou Japan
Ian En-Hsu Yen United States
Shangwen Lv China
Carl Sable relative to Tianlei Hu China Tianlei Hu's profile →
Citations per field
00.5×1.5×1.8×
Tianlei Hu · 1×
Citations per year

Countries citing papers authored by Carl Sable

Since Specialization
Citations

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

Fields of papers citing papers by Carl Sable

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Carl Sable, 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 Carl Sable Line = papers co-authored together Carl Sable links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2002181
2
Beyond information retrieval--medical question answering.
200680
3 199961
4 200823
5 199922
6 200018
7 201115
8 200211
9 20199
10 20018
11
Question analysis for biomedical question answering.
20054
12 20032
13 20022

About Carl Sable

Carl Sable is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, General Health Professions, Information Systems and Molecular Biology, having authored 13 papers that have together received 436 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (4 papers), Text and Document Classification Technologies (4 papers), Advanced Text Analysis Techniques (2 papers), Topic Modeling (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Natural Language Processing Techniques (2 papers), Health Sciences Research and Education (2 papers) and Spam and Phishing Detection (1 paper). The work is most often cited by research in Artificial Intelligence (294 citations), Computer Vision and Pattern Recognition (138 citations), Information Systems (115 citations), Signal Processing (38 citations) and Health Informatics (2 citations). Carl Sable has collaborated with scholars based in United States. Frequent co-authors include Vasileios Hatzivassiloglou, Kathleen McKeown, Barry Schiffman, Regina Barzilay, Ani Nenkova, David K. Evans, Judith L. Klavans, Hong Yu, Vijay Shanker and John Ely. Their work appears in journals such as JACC: Cardiovascular Interventions, International Journal on Digital Libraries, Lecture notes in computer science, Columbia Academic Commons (Columbia University) and PubMed.

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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