L V Ackerman

1.1k citations
33 papers · 815 · h-index 16

Impact in

Papers in

L V Ackerman

32 papers receiving 730 citations

Peers

L V Ackerman
Comparison fields: 5 of 100
  • Radiology, Nuclear Medicine and Imaging 290
  • Oral Surgery 85
  • Rheumatology 160
  • Pulmonary and Respiratory Medicine 287
  • Computer Vision and Pattern Recognition 191
Replace Xiangrong Zhou with:
Xiangrong Zhou Japan
Ashraf Mohamed United States
Alan Brett United Kingdom
Jifke F. Veenland Netherlands
Tatsuro Hayashi Japan
Alessandro Stefano Italy
Karl Fritscher Austria
Marijn van Stralen Netherlands
Pieter Slagmolen Belgium
L V Ackerman relative to Xiangrong Zhou Japan Xiangrong Zhou's profile →
Citations per field
00.5×8.4×
Xiangrong Zhou · 1×
Citations per year

Countries citing papers authored by L V Ackerman

Since Specialization
Citations

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

Fields of papers citing papers by L V Ackerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992106
2 199389
3 199184
4 199563
5 198053
6 197252
7 197744
8 197944
9 198643
10
Proliferating benign and malignant epithelial lesions of the oral cavity.
195829
11 198729
12 198527
13 197327
14 197625
15 198519
16 197118
17 19778
18 19888
19 19927
20 19827

About L V Ackerman

L V Ackerman is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Computer Vision and Pattern Recognition and Cancer Research, having authored 33 papers that have together received 815 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (7 papers), Digital Radiography and Breast Imaging (7 papers), AI in cancer detection (6 papers), Radiology practices and education (5 papers), Breast Cancer Treatment Studies (5 papers), Image Retrieval and Classification Techniques (4 papers), Breast Lesions and Carcinomas (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (290 citations), Oral Surgery (85 citations), Rheumatology (160 citations), Pulmonary and Respiratory Medicine (287 citations) and Computer Vision and Pattern Recognition (191 citations). L V Ackerman has collaborated with scholars based in United States and France. Frequent co-authors include A. Ardeshir Goshtasby, Earl E. Gose, David Turner, Michael Kyriakos, John L. Semmlow, L G Shapeero, D. Vanel, G Contesso, D. Couanet and Malcolm H. McGavran. Their work appears in journals such as Radiology, Cancer, Journal of Computer Assisted Tomography, IEEE Transactions on Medical Imaging and Journal of neurosurgery.

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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