2019 |
Fernandez-Lozano, C; Carballal, A; Munteanu, CR.; Gestal, M; Maojo, V; Pazos, A Machine Learning in Biomedical Informatics Capítulo de libro En: Narayan, Roger (Ed.): Encyclopedia of Biomedical Engineering, pp. 389 - 399, Elsevier, 2019, ISBN: 978-0-12-805144-3. Resumen | Enlaces | BibTeX | Etiquetas: Classification, Decision trees, Deep learning, Knowledge discovery, Machine learning, Medical data acquisition, Medical data analysis, Random Forest, Regression, Reinforcement learning, Supervised learning, Support Vector Machines, Unsupervised learning @inbook{FERNANDEZLOZANO2019389,Biomedical informatics has skyrocketed in the last years by reducing sequencing costs with next-generation sequencing techniques. Thus, the amount of available data to study is increasing excessively, and more recently, is even open access for researchers. Due to this, biomedical informatics researchers, with different profiles, are using machine learning algorithms for knowledge extraction and, despite the great amount of benefits this entails, it also requires to take into account a series of particularities of inexcusable compliance in order to achieve a solution which is real. |
2019 |
Machine Learning in Biomedical Informatics Capítulo de libro En: Narayan, Roger (Ed.): Encyclopedia of Biomedical Engineering, pp. 389 - 399, Elsevier, 2019, ISBN: 978-0-12-805144-3. |