@inproceedings{c8a4fcf46f574c8e8089c8e262eac4e5,
title = "Translational Challenges of Biomedical Machine Learning Solutions in Clinical and Laboratory Settings",
abstract = "The ever increasing use of artificial intelligence (AI) methods in biomedical sciences calls for closer inter-disciplinary collaborations that transfer the domain knowledge from life scientists to computer science researchers and vice-versa. We highlight two general areas where the use of AI-based solutions designed for clinical and laboratory settings has proven problematic. These are used to demonstrate common sources of translational challenges that often stem from the differences in data interpretation between the clinical and research view, and the unmatched expectations and requirements on the result quality metrics. We outline how explicit interpretable inference reporting might be used as a guide to overcome such translational challenges. We conclude with several recommendations for safer translation of machine learning solutions into real-world settings.",
keywords = "Biomedicine, Machine learning",
author = "Carlos Vega and Miroslav Kratochvil and Venkata Satagopam and Reinhard Schneider",
note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 9th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2022 ; Conference date: 27-06-2022 Through 30-06-2022",
year = "2022",
doi = "10.1007/978-3-031-07802-6_30",
language = "English",
isbn = "9783031078019",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "353--358",
editor = "Ignacio Rojas and Olga Valenzuela and Fernando Rojas and Herrera, {Luis Javier} and Francisco Ortu{\~n}o",
booktitle = "Bioinformatics and Biomedical Engineering - 9th International Work-Conference, IWBBIO 2022, Proceedings",
address = "Germany",
}