This is a list of my academic work. For talks and similar, visit the talks page.

I defended my Ph. D. in February, 2019. My dissertation is called Small data: practical modeling issues in human-model -omic data.

Papers, etc.

• Pedersen BR, Holsbø E, Andersen T, Shvetsov N, Ravn J, Sommerseth HL, Bongo LA. Lessons Learned Developing and Using a Machine Learning Model to Automatically Transcribe 2.3 Million Handwritten Occupation Codes. (data) Historical Life Course Studies 2022; Volum 11. ISSN 2352-6343.s 1 - 17.s
• Holsbø E, Olsen KS. Metastatic Breast Cancer and Pre-Diagnostic Blood Gene Expression Profiles—The Norwegian Women and Cancer (NOWAC) Post-Genome Cohort. Frontiers in oncology. 2020 Oct 15;10:2277.
• Holsbø E., Perduca V., Bongo L. A., Lund E., & Birmelé E. (2020). Predicting breast cancer metastasis from whole-blood transcriptomic measurements. BMC Research Notes, 13(1), 1-5.
• Dong C, Metzger M, Holsbø E, Perduca V, Carbonnel F. Systematic review with meta‐analysis: mortality in acute severe ulcerative colitis. Aliment Pharmacol Ther. 2019; 00: 1– 27.
• Jácome C., Ravn J., Holsbø E., Aviles-Solis J. C., Melbye, H. & Bongo, L. A. Convolutional Neural Network for Breathing Phase Detection in Lung Sounds. Sensors 19, (2019). [arXiv]
• Holsbø E., & Perduca V. (2018). Shrinkage estimation of rate statistics. Case Studies in Business, Industry & Government Statistics, 7(1). [arXiv]
• M. Grønnesby, J. C. A. Solis, E. Holsbø, H. Melbye, and L. A. Bongo, Machine Learning Based Crackle Detection in Lung Sounds, [arXiv], May 2017. Currently under submission.
• H. M. Bøvelstad, E. Holsbø, L. A. Bongo, and E. Lund, A Standard Operating Procedure For Outlier Removal In Large-Sample Epidemiological Transcriptomics Datasets, [bioRxiv], May 2017. Hege Bøvelstad and I are joint first authors.
• E. Holsbø, V. Perduca, L. A. Bongo, E. Lund, and E. Birmelé, Curve Selection For Predicting Breast Cancer Metastasis From Prospective Gene Expression in Blood. [bioRxiv], 2017.
• Tartari G, Tiede L, Holsbø E, Knudsen K, Raknes IA, Fjukstad B, Mode N, Bjørndalen JM, Lund E, and Bongo LA. Mr. Clean: A Tool for Tracking and Comparing the Lineage of Scientific Visualization Code. 2nd IEEE Working Conference on Software Visualization
• Elahi N, Karlsen R, and Holsbø E. Personalized Photo Recommendation By Leveraging User Modeling On Social Network. Proceedings of the iiWAS2013 The 15th International Conference on Information Integration and Web-based Applications & Services.
• Holsbø E, Ha PH, and Anshus O. The Big Digger & Puzzler System for Harvesting & Analyzing Data from Social Networks. Norsk informatikkonferanse NIK 2013

Book chapter

• Holsbø E, Møllersen K. Woes of The Practicing Omics Researcher. Universitetsforlaget 2020 ISBN 978-82-15-04119-3.s 77 - 94.
• Fjukstad B, Shvetsov N, Nøst TH, Bøvelstad HM, Halbach T, Holsbø E, Hansen, K, Bongo, LA. Reproducible Data Management and Analysis using R. Universitetsforlaget 2020 ISBN 978-82-15-04119-3.s 48 - 62.s

Other

• Dong C, Metzger M, Holsbø E, Perduca V, Carbonnel Fr. Letter: how can we reduce mortality in elderly patients with acute severe ulcerative colitis? Authors’ reply. Alimentary Pharmacology and Therapeutics 2020; Volum 51 (12). ISSN 0269-2813.s 1445 - 1446.s
• Olsen KS, Holsbø E, Rognmo K, Krum-Hansen S, and Lund E. Stress related to a suspicious mammogram - potential transcriptomic effects. Abstract. The 7th Conference on Epidemiology and Registry-Based Health Research - NordicEpi 2015

As adviser

• Elias E.G. Riise, Improving automated underwater ship hull inspection through incremental learning & uncertainty quantification in deep learning models. Master thesis, 2023.
• Erling Devold, Through Space and Time. Master thesis, 2023
• Tengel Skar, Scalable exploration of population-scale drug consumption data. Master thesis, 2019.
• Mike Voets, Deep Learning: From Data Extraction to Large-Scale Analysis. Master thesis, 2018.
• Morten Grønnesby, Automated Lung Sound Analysis. Master thesis, 2016.