Objective: Evaluating the possibility of predicting chronic rhinosinusitis with nasal polyps (CRSwNP) disease course using Artificial Intelligence.
Methods: We prospectively included patients undergoing first endoscopic sinus surgery (ESS) for nasal polyposis. Preoperative (demographic data, blood eosinophiles, endoscopy, Lund-Mackay, SNOT-22 and depression PHQ scores) and follow-up data was standardly collected.
Species turnover is ubiquitous. However, it remains unknown whether certain types of species are consistently gained or lost across different habitats. Here, we analysed the trajectories of 1827 plant species over time intervals of up to 78 years at 141 sites across mountain summits, forests, and lowland grasslands in Europe.
View Article and Find Full Text PDFCurrent analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked.
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