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Cost-sensitive ordinal classification methods to predict SARS-CoV-2 pneumonia severity

García, F.; Lee, D.J.; España Yandiola, P.P.; Urrutia Landa, I.; Martínez-Minaya, J.; Hayet-Otero, M.; Nieves Ermecheo, M.; Quintana, J.M.; Menéndez, R.; Torres, A.; Zalacain Jorge, R. (2024-02-08)

Objective: To study the suitability of cost-sensitive ordinal artificial intelligence-machine learning (AI-ML) strategies in the prognosis of SARS-CoV-2 pneumonia severity. Materials & methods: Observational, retrospective,...

Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods

García, F.; Lee, D.J.; Mendoza Garcés, F.; García-Gutiérrez, S. (2024-03-01)

Background: Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity. Objective: To...

Banach function spaces done right

Lorist, E.; Nieraeth, Z. (2024-03-01)

In this survey, we discuss the definition of a (quasi-)Banach function space. We advertise the original definition by Zaanen and Luxemburg, which does not have various issues introduced by other, subsequent definitions. More...

Indoor Localization System With NLOS Mitigation Based on Self-Training

Huang, Y.; Mazuelas, S.; Ge, F.; Shen, Y. (2023-07-01)

Location-awareness has become a fundamental requirement for multiple emerging applications with the rapid development of wireless technologies. The high-accuracy ranging enabled by ultra-wide bandwidth (UWB) signals is ofte...