Search results for "predictive modelling"
showing 10 items of 35 documents
Soil erosion modelling: a global review and statistical analysis
2021
40 Pags.- 10 Figs.- 2 Tabls.- Suppl. Informat. The definitive version is available at: https://www.sciencedirect.com/science/journal/00489697
A Machine Learning Model to Predict Intravenous Immunoglobulin-Resistant Kawasaki Disease Patients: A Retrospective Study Based on the Chongqing Popu…
2021
Objective: We explored the risk factors for intravenous immunoglobulin (IVIG) resistance in children with Kawasaki disease (KD) and constructed a prediction model based on machine learning algorithms.Methods: A retrospective study including 1,398 KD patients hospitalized in 7 affiliated hospitals of Chongqing Medical University from January 2015 to August 2020 was conducted. All patients were divided into IVIG-responsive and IVIG-resistant groups, which were randomly divided into training and validation sets. The independent risk factors were determined using logistic regression analysis. Logistic regression nomograms, support vector machine (SVM), XGBoost and LightGBM prediction models wer…
On the relationship between some production parameters and a vegetation index in viticulture
2013
The use and timing of many agronomical practices such as the scheduling of irrigation and harvesting are dependent on accurate vineyard sampling of qualitative and productive parameters. Crop forecasting also depends on the representativeness of vineyard samples during the whole phenological period. This manuscript summarizes the last two years of precision viticulture in Sicily (Italy); agronomic campaigns were carried out in 2012 and 2013 within the "Tenute Rapitalà" and "Donnafugata" farms. Normalized Difference Vegetation Index derived from satellite images (RapidEye) acquired at berry set, pre-veraison and ripening phenological stages (occurred at June, July and August respectively) ha…
The use of prediction models of spontaneous pregnancy in in vitro fertilization units reveals differences between the expected results of public and …
2009
To evaluate the applicability of prediction models (PM) of spontaneous pregnancy (SP) in a population of infertile patients from a university-affiliated private assisted reproductive technology center (Instituto Valenciano de Infertilidad) and in the reproductive medicine section of a public university hospital (La Fe), both belonging to the same city (Valencia, Spain) between January and December 2008. We calculated the probability of SP using the PM developed by Hunault et al. in our two populations, and observed an estimated probability of SP40% or the PM applicable in approximately 97% of the studied couples, and statistical differences between pregnancy probabilities in the two setting…
Enhanced prediction of hemoglobin concentration in a very large cohort of hemodialysis patients by means of deep recurrent neural networks.
2019
Erythropoiesis Stimulating Agents (ESAs) have become a standard anemia management tool for End Stage Renal Disease (ESRD) patients. However, dose optimization constitutes an extremely challenging task due to huge inter and intra-patient variability in the responses to ESA administration. Current data-based approaches to anemia control focus on learning accurate hemoglobin prediction models, which can be later utilized for testing competing treatment choices and choosing the optimal one. These methods, despite being proven effective in practice, present several shortcomings which this paper intends to tackle. Namely, they are limited to a small cohort of patients and, even then, they fail to…
Technical Note: Prediction Models of Airborne Sound Insulation of Multilayer Materials with Viscoelastic Thin Sheets
2008
The growing introduction of new insulation materials in building acoustics has caused an increase of the importance of the prediction tools. Appropriate simulations allow strictly necessary laboratory measurements to be identified. In this way, costs are reduced. The demands of new legislation has resulted in the appearance of various software designed to facilitate prediction. The prediction models are based on different hypotheses: adaptation of impedances, spatial behaviour of spectral components, statistical energy distribution, the Finite Element Method (FEM), etc. Each of these models and methods offer advantages and contain limitations. In this paper, different models for prediction…
Probabilité d'apparition d'un phénomène parasitaire et choix de modèles de régression logistique
2007
Epidemiological processes are now using spatial statistics and modelling tools. The main objective of most health risks studies consists in identifying potential contamination sources and factors capable of explaining their localization. Health data often prove binary (typically presence/absence) and specific methods such as binary logistic regression have to be used. This method's output consists in a probability for the pathogen of interest. A posterior classification of each sample is then conducted using a probability threshold. The method used to maximize this threshold is called the ROC curve which consists in giving a representation of the behaviour of the model and then to choose th…
Towards the improvement of food flavour analysis: Modelling chemical and sensory data and expert knowledge integration
2019
International audience
Dynamic mean absolute error as new measure for assessing forecasting errors
2018
Abstract Accurate wind power forecast is essential for grid integration, system planning, and electricity trading in certain electricity markets. Therefore, analyzing prediction errors is a critical task that allows a comparison of prediction models and the selection of the most suitable model. In this work, the temporal error and absolute magnitude error are simultaneously considered to assess the forecast error. The trade-off between both types of errors is computed, analyzed, and interpreted. Moreover, a new index, the dynamic mean absolute error, DMAE, is defined to measure the prediction accuracy. This index accounts for both error components: temporal and absolute. Real cases of wind …
Making Every "Point" Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
2019
Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men’s wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modelling. The valid and reliable template developed by Francis, Owen and Peters (2019) was used to analyse video footage in S…