Louisa Bolm
About
Louisa Bolm is a scholar working on Oncology, Surgery and Pulmonary and Respiratory Medicine.
According to data from OpenAlex, Louisa Bolm has authored 78 papers receiving a total of 783 indexed citations (citations by other indexed papers that have themselves been cited), including 71 papers in Oncology, 44 papers in Surgery and 28 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Louisa Bolm's work include Pancreatic and Hepatic Oncology Research (62 papers), Pancreatitis Pathology and Treatment (27 papers) and Neuroendocrine Tumor Research Advances (14 papers). Louisa Bolm is often cited by papers focused on Pancreatic and Hepatic Oncology Research (62 papers), Pancreatitis Pathology and Treatment (27 papers) and Neuroendocrine Tumor Research Advances (14 papers). Louisa Bolm collaborates with scholars based in Germany, United States and Ukraine. Louisa Bolm's co-authors include Ulrich F. Wellner, Tobias Keck, Dirk Rades, Dirk Bausch, Kim C. Honselmann, Peter Bronsert, Hryhoriy Lapshyn, Lukas Käsmann, Ekaterina Petrova and Steven E. Schild and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gastroenterology and PLoS ONE.
In The Last Decade
Louisa Bolm
70 papers receiving 771 citations
Peers
Louisa Bolm
Hideki Kamada Japan
Kim C. Honselmann Germany
J. Furuse Japan
Gregory Sergeant Belgium
Ui Sup Shin South Korea
Sadaaki Yamazoe Japan
Lingdi Yin China
Masato Matsuyama Japan
Shoichi Dowaki Japan
F. Cvitkovic France
Citations per year, relative to Louisa Bolm Louisa Bolm (= 1×)
peers
Hideki Kamada
Countries citing papers authored by Louisa Bolm
Since
Specialization
Citations
This map shows the geographic impact of Louisa Bolm'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 Louisa Bolm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Louisa Bolm more than expected).
Fields of papers citing papers by Louisa Bolm
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Louisa Bolm. 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 Louisa Bolm. The network helps show where Louisa Bolm may publish in the future.
Co-authorship network of co-authors of Louisa Bolm
This figure shows the co-authorship network connecting the top 25 collaborators of Louisa Bolm. A scholar is included among the top collaborators of Louisa Bolm based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Louisa Bolm. Louisa Bolm is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Bolm, Louisa, et al.. (2025). Which technical difficulty score can best predict postoperative outcomes after minimally invasive liver resections?. Langenbeck s Archives of Surgery. 410(1). 79–79.
2.
Strasser, Jon, Rüdiger Braun, Kim C. Honselmann, et al.. (2025). Adjuvant Chemotherapy Is Associated with Improved Survival in Advanced Ampullary Adenocarcinoma—A Population-Based Analysis by the German Cancer Registry Group. Journal of Clinical Medicine. 14(11). 3869–3869.
3.
Tustumi, Francisco, Louisa Bolm, Felipe B. Maegawa, et al.. (2025). Global strategies for the diffusion of robotic surgery. ABCD Arquivos Brasileiros de Cirurgia Digestiva (São Paulo). 38. e1908–e1908.
4.
Honselmann, Kim C., Louisa Bolm, Rüdiger Braun, et al.. (2025). An R0 resection margin does improve overall survival after PDAC resection– real-world evidence from 6.000 cases from the German Cancer Registry Group. European Journal of Surgical Oncology. 51(6). 109693–109693.
5.
Bolm, Louisa, Rüdiger Braun, Kim C. Honselmann, et al.. (2025). Perioperative and oncologic outcomes after total pancreatectomy and pancreatoduodenectomy for pancreatic head adenocarcinoma—A propensity score–matched analysis from the German Cancer Registry Group. Surgery. 181. 109292–109292.
6.
Bronsert, Peter, Oliver Schilling, Kim C. Honselmann, et al.. (2024). Postoperative pancreatic fistula risk assessment using digital pathology based analyses at the parenchymal resection margin of the pancreas – Results from the randomized multicenter RECOPANC trial. HPB. 27(3). 393–401.
7.
Klinkhammer‐Schalke, Monika, Sylke Ruth Zeißig, Kim C. Honselmann, et al.. (2024). Oncological Outcomes and Patterns of Recurrence after the Surgical Resection of an Invasive Intraductal Papillary Mucinous Neoplasm versus Primary Pancreatic Ductal Adenocarcinoma: An Analysis from the German Cancer Registry Group of the Society of German Tumor Centers. Cancers. 16(11). 2016–2016.
8.
Bolm, Louisa, Monika Klinkhammer‐Schalke, Sylke Ruth Zeißig, et al.. (2024). When Should Lymphadenectomy Be Performed in Non-Metastatic Pancreatic Neuroendocrine Tumors? A Population-Based Analysis of the German Clinical Cancer Registry Group. Cancers. 16(2). 440–440.
9.
Wellner, Ulrich F., et al.. (2023). Minimally invasive approaches in pancreatic cancer surgery. European surgery. Supplement/European surgery. 56(3-4). 76–85.
10.
Honselmann, Kim C., et al.. (2023). Recent onset diabetes is associated with better survival in pancreatic ductal adenocarcinoma—An analysis of preoperative symptoms within the DGAV StuDoQ|Pancreas Registry. Surgery. 174(3). 674–683.
11.
Bolm, Louisa, Kim C. Honselmann, Birte Kulemann, et al.. (2023). The impact of intra- and postoperative fluid balance in pancreatic surgery - A retrospective cohort study. Pancreatology. 23(6). 689–696.
12.
Lillemoe, Keith D., Carlos Fernández‐del Castillo, Kim C. Honselmann, et al.. (2023). The impact of surgical-oncologic textbook outcome in patients with stage I to III pancreatic ductal adenocarcinoma: A cross-validation study of two national registries. Surgery. 175(4). 1120–1127.
13.
Braun, Rüdiger, Maren Drenckhan, Axel Künstner, et al.. (2023). Establishment and Molecular Characterization of Two Patient-Derived Pancreatic Ductal Adenocarcinoma Cell Lines as Preclinical Models for Treatment Response. Cells. 12(4). 587–587.
14.
Fong, Zhi Ven, Gabriella Lionetto, Louisa Bolm, et al.. (2023). 1178 LYMPH NODE YIELD IS ASSOCIATED WITH IMPROVED OVERALL SURVIVAL AND INCREASED TIME TO RECURRENCE IN NODE-NEGATIVE PANCREATIC DUCTAL ADENOCARCINOMA FOLLOWING NEOADJUVANT THERAPY. Gastroenterology. 164(6). S–1512.
15.
Braun, Rüdiger, Monika Klinkhammer‐Schalke, Sylke Ruth Zeißig, et al.. (2022). Clinical Outcome and Prognostic Factors of Pancreatic Adenosquamous Carcinoma Compared to Ductal Adenocarcinoma—Results from the German Cancer Registry Group. Cancers. 14(16). 3946–3946.
16.
Lapshyn, Hryhoriy, Michael Thomaschewski, Ekaterina Petrova, et al.. (2021). A simple preoperative stratification tool predicting the risk of postoperative pancreatic fistula after pancreatoduodenectomy. Pancreatology. 21(5). 957–964.
17.
Petrova, Ekaterina, Rüdiger Braun, Kim C. Honselmann, et al.. (2021). Survival Outcome and Prognostic Factors for Pancreatic Acinar Cell Carcinoma: Retrospective Analysis from the German Cancer Registry Group. Cancers. 13(23). 6121–6121.
18.
Lapshyn, Hryhoriy, Ekaterina Petrova, Kim C. Honselmann, et al.. (2020). Radiological prediction of portal vein infiltration in patients with pancreatic ductal adenocarcinoma. Pancreatology. 21(1). 155–162.
19.
Bolm, Louisa, Katharina Mueller, Ekaterina Petrova, et al.. (2020). Systematic Analysis of Accuracy in Predicting Complete Oncological Resection in Pancreatic Cancer Patients—Proposal of a New Simplified Borderline Resectability Definition. Cancers. 12(4). 882–882.
20.
Wellner, Ulrich F., Tobias Krauß, Ágnes Csanádi, et al.. (2016). Mesopancreatic Stromal Clearance Defines Curative Resection of Pancreatic Head Cancer and Can Be Predicted Preoperatively by Radiologic Parameters. Medicine. 95(3). e2529–e2529.
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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