Author:
Colliot Olivier,Thibeau-Sutre Elina,Burgos Ninon
Abstract
AbstractReproducibility is a cornerstone of science, as the replication of findings is the process through which they become knowledge. It is widely considered that many fields of science are undergoing a reproducibility crisis. This has led to the publications of various guidelines in order to improve research reproducibility.This didactic chapter intends at being an introduction to reproducibility for researchers in the field of machine learning for medical imaging. We first distinguish between different types of reproducibility. For each of them, we aim at defining it, at describing the requirements to achieve it, and at discussing its utility. The chapter ends with a discussion on the benefits of reproducibility and with a plea for a nondogmatic approach to this concept and its implementation in research practice.
Reference80 articles.
1. Seab J, Jagust W, Wong S, Roos M, Reed BR, Budinger T (1988) Quantitative NMR measurements of hippocampal atrophy in Alzheimer’s disease. Magn Reson Med 8(2):200–208
2. Lehericy S, Baulac M, Chiras J, Pierot L, Martin N, Pillon B, Deweer B, Dubois B, Marsault C (1994) Amygdalohippocampal MR volume measurements in the early stages of Alzheimer disease. Am J Neuroradiol 15(5):929–937
3. Jack CR, Petersen RC, Xu YC, Waring SC, O’Brien PC, Tangalos EG, Smith GE, Ivnik RJ, Kokmen E (1997) Medial temporal atrophy on MRI in normal aging and very mild alzheimer’s disease. Neurology 49(3):786–794
4. Varoquaux G, Colliot O (2022) Evaluating machine learning models and their diagnostic value. HAL preprint hal-03682454. https://hal.archives-ouvertes.fr/hal-03682454/
5. Thibeau-Sutre E, Diaz M, Hassanaly R, Routier A, Dormont D, Colliot O, Burgos N (2022) ClinicaDL: an open-source deep learning software for reproducible neuroimaging processing. Comput Methods Prog Biomed 220:106818
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献