B. Michael Kelm

2.5k citations
19 papers · 1.4k · 1 hit paper · h-index 13

Impact in

Papers in

B. Michael Kelm

19 papers receiving 1.3k citations

B. Michael Kelm's Hit Papers

A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data 2009 · 929 citations
9290+5+11Years since publication250500750

Peers

B. Michael Kelm
Comparison fields: 5 of 177
  • Radiology, Nuclear Medicine and Imaging 260
  • Health Informatics 15
  • Biophysics 55
  • Analytical Chemistry 79
  • Health Information Management 31
Replace Sidike Paheding with:
Sidike Paheding United States
Michał Grochowski Poland
Agnieszka Mikołajczyk Poland
Minghui Hu China
Nahian Siddique United States
Tzu-Tsung Wong Taiwan
Zewen Li China
A. K. Malik India
Ying Xue China
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Countries citing papers authored by B. Michael Kelm

Since Specialization
Citations

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

Fields of papers citing papers by B. Michael Kelm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by B. Michael Kelm. 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 B. Michael Kelm. The network helps show where B. Michael Kelm may publish in the future.

Co-authors

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

All Works

19 of 19 papers shown
#Work
1
A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data
Hit paper breakdown →
2009929
2 201276
3 201656
4 201156
5 200943
6 200635
7 200827
8 200623
9 201719
10 201318
11 200618
12 201414
13 201214
14 201112
15 20098
16 20065
17 20125
18 20123
19
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers
20171

About B. Michael Kelm

B. Michael Kelm is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Biomedical Engineering, Computer Vision and Pattern Recognition and Surgery, having authored 19 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (6 papers), MRI in cancer diagnosis (3 papers), Medical Imaging and Analysis (3 papers), AI in cancer detection (3 papers), Cardiac Imaging and Diagnostics (3 papers), Medical Image Segmentation Techniques (2 papers), Remote-Sensing Image Classification (2 papers) and Advanced Neuroimaging Techniques and Applications (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (260 citations), Health Informatics (15 citations), Biophysics (55 citations), Analytical Chemistry (79 citations) and Health Information Management (31 citations). B. Michael Kelm has collaborated with scholars based in Germany, United States and Belgium. Frequent co-authors include Bjoern Menze, Fred A. Hamprecht, Peter Bachert, Uwe Himmelreich, Wolfgang Petrich, Yefeng Zheng, Dorin Comaniciu, Michael Wels, Christian M. Zechmann and Michael Suehling. Their work appears in journals such as Magnetic Resonance in Medicine, NMR in Biomedicine, Medical Physics, IEEE Transactions on Medical Imaging and Medical Image Analysis.

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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