Trusting Machine Learning Results from Medical Procedures in the Operating Room

no code implementations • 4 Jan 2022 • Ali El-Merhi, Helena Odenstedt Hergés, Linda Block, Mikael Elam, Richard Vithal, Jaquette Liljencrantz, Miroslaw Staron

Machine learning can be used to analyse physiological data for several purposes.

BIG-bench Machine Learning

Towards Trustworthy Cross-patient Model Development

no code implementations • 20 Dec 2021 • Ali El-Merhi, Helena Odenstedt Hergés, Linda Block, Mikael Elam, Richard Vithal, Jaquette Liljencrantz, Miroslaw Staron

The results show that patients' demographics has a large impact on the performance and explainability and thus trustworthiness.

Empirical Standards for Software Engineering Research

1 code implementation • 7 Oct 2020 • Paul Ralph, Nauman bin Ali, Sebastian Baltes, Domenico Bianculli, Jessica Diaz, Yvonne Dittrich, Neil Ernst, Michael Felderer, Robert Feldt, Antonio Filieri, Breno Bernard Nicolau de França, Carlo Alberto Furia, Greg Gay, Nicolas Gold, Daniel Graziotin, Pinjia He, Rashina Hoda, Natalia Juristo, Barbara Kitchenham, Valentina Lenarduzzi, Jorge Martínez, Jorge Melegati, Daniel Mendez, Tim Menzies, Jefferson Molleri, Dietmar Pfahl, Romain Robbes, Daniel Russo, Nyyti Saarimäki, Federica Sarro, Janet Siegmund, Diomidis Spinellis, Miroslaw Staron, Klaas Stol, Margaret-Anne Storey, Davide Taibi, Damian Tamburri, Marco Torchiano, Christoph Treude, Burak Turhan, XiaoFeng Wang, Sira Vegas

Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e. g. a questionnaire survey).

Software Engineering General Literature