Timo Gaiser

9.9k citations
134 papers · 3.7k indexed · 2 hit papers · h-index 28

Timo Gaiser

131 papers receiving 3.6k citations

Hit Papers

Predicting survival from colorectal cancer histology slid...6112016202620192022200400600

Peers

Timo Gaiser
Comparison fields: 5 of 132
  • Oncology 1.4k
  • Health Informatics 61
  • Cancer Research 625
  • Radiology, Nuclear Medicine and Imaging 868
  • Gastroenterology 175
Replace Shumpei Ishikawa with:
Shumpei Ishikawa Japan
Esther Herpel Germany
Toby C. Cornish United States
Niels Halama Germany
Maode Lai China
Karin A. Oien United Kingdom
Håvard E. Danielsen Norway
Stephen Yip Canada
Julien Caldéraro France
Mohammad Ilyas United Kingdom
Timo Gaiser relative to Shumpei Ishikawa Japan Shumpei Ishikawa's profile →
Citations per field
00.5×1.5×2.4×
Shumpei Ishikawa · 1×
Citations per year

Countries citing papers authored by Timo Gaiser

Since Specialization
Citations

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

Fields of papers citing papers by Timo Gaiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20235
3 20221
4 20225
5 20211
6 202013
7 20206
8 201910
9 201916
10
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter studybreakdown →
2019611
11 201918
12 201819
13 201815
14 201738
15 20179
16 201616
17 201276
18 200793
19
[Her-2/neu analysis--new data?].
20061
20 200217

About Timo Gaiser

Timo Gaiser is a scholar working on Oncology, Gastroenterology and Pathology and Forensic Medicine, having authored 134 papers that have together received 3.7k indexed citations. Recurring topics across this work include Gastric Cancer Management and Outcomes (24 papers), Genetic factors in colorectal cancer (20 papers), Cancer Genomics and Diagnostics (16 papers), Colorectal Cancer Treatments and Studies (14 papers), HER2/EGFR in Cancer Research (11 papers), Gastrointestinal Tumor Research and Treatment (10 papers), Esophageal Cancer Research and Treatment (10 papers) and Radiomics and Machine Learning in Medical Imaging (10 papers). The work is most often cited by research in Oncology (1.4k citations), Health Informatics (61 citations) and Cancer Research (625 citations). Timo Gaiser has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Markus D. Siegelin, Alexander Marx, Jakob Nikolas Kather, Cleo‐Aron Weis, Antje Habel, Daniela Hirsch, Susanne Melchers, Esther Herpel, Thomas Ried and Inka Zörnig. Their work appears in journals such as Journal of Clinical Oncology, Annals of Oncology, International Journal of Cancer, European Journal of Cancer and Oncotarget.

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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