DENDRITIC CELL POPULATIONS IN PATIENTS WITH SELF-REPORTED FOOD HYPERSENSITIVITY



Basic Statistical Estimation Outperforms Machine Learning in Monthly Prediction of Seasonal Climatic Parameters

Machine learning (ML) has been utilized to predict climatic parameters, and many successes HERBAL D-TOX have been reported in the literature.In this paper, we scrutinize the effectiveness of five widely used ML algorithms in the monthly prediction of seasonal climatic parameters using monthly image data.Specifically, we quantify the predictive perf

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Analyzing the Saturation of Growing Stem Volume Based on ZY-3 Stereo and Multispectral Images in Planted Coniferous Forest

Recently, remote sensing (RS) technology are becoming an increasingly important technology in estimating forest growing stem volume (GSV), and the saturation issue of spectral variables from various optical sensors severely hinders the improvement of mapping forest GSV, especially in the planted forest with high GSV.Forest canopy height is widely c

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