Lars Asker

1.0k citations
35 papers · 547 · h-index 12

Impact in

Papers in

    • Natural Language Processing Techniques 8
    • Topic Modeling 6
    • Machine Learning in Healthcare 6
    • Text and Document Classification Technologies 4
    • Imbalanced Data Classification Techniques 4
    • Biomedical Text Mining and Ontologies 7

Lars Asker

35 papers receiving 489 citations

Peers

Lars Asker
Comparison fields: 5 of 89
  • Toxicology 62
  • Health Informatics 17
  • Artificial Intelligence 395
  • Health Information Management 41
  • Signal Processing 54
Replace Zongcheng Ji with:
Zongcheng Ji China
Isak Karlsson Sweden
Michael R. Smith United States
Asma Ben Abacha United States
Jianfu Li United States
G. William Moore United States
Lothar Gierl Germany
Urszula Chajewska United States
Lars Asker relative to Zongcheng Ji China Zongcheng Ji's profile →
Citations per field
00.5×3.6×
Zongcheng Ji · 1×
Citations per year

Countries citing papers authored by Lars Asker

Since Specialization
Citations

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

Fields of papers citing papers by Lars Asker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Lars Asker, 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 Lars Asker Line = papers co-authored together Lars Asker 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 200296
2 201460
3 199860
4 201657
5 201551
6 200238
7
Handling Temporality of Clinical Events for Drug Safety Surveillance.
201527
8 201423
9 200920
10
Exploiting Syntax when Detecting Protein Names in Text
200219
11
Ensembles as a sequence of classifiers
199717
12 200714
13 19979
14 20098
15
Applying machine learning to Amharic text classification
20065
16 20155
17 20174
18
Applying Methods for Signal Detection in Spontaneous Reports to Electronic Patient Records
20134
19 20053
20
Intelligent Data Analysis in Medicine and Pharmacology
20023

About Lars Asker

Lars Asker is a scholar working on Artificial Intelligence, Molecular Biology, Toxicology, Information Systems and Management Science and Operations Research, having authored 35 papers that have together received 547 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (8 papers), Biomedical Text Mining and Ontologies (7 papers), Topic Modeling (6 papers), Machine Learning in Healthcare (6 papers), Pharmacovigilance and Adverse Drug Reactions (5 papers), Text and Document Classification Technologies (4 papers), Imbalanced Data Classification Techniques (4 papers) and Data Mining Algorithms and Applications (3 papers). The work is most often cited by research in Toxicology (62 citations), Health Informatics (17 citations), Artificial Intelligence (395 citations), Health Information Management (41 citations) and Signal Processing (54 citations). Lars Asker has collaborated with scholars based in Sweden, United States and Mozambique. Frequent co-authors include Henrik Boström, Fredrik Olsson, Jing Zhao, Panagiotis Papapetrou, Gunnar Eriksson, Aron Henriksson, Richard Maclin, Kai Puolamäki, Andreas Henelius and Björn Gambäck. Their work appears in journals such as Data Mining and Knowledge Discovery, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Machine Learning, Violence and Victims and Journal of Biomedical Informatics.

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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