Search results for "Predictive modelling"
showing 10 items of 35 documents
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…
Validation and update of the thoracic surgery scoring system (Thoracoscore) risk model.
2020
Abstract OBJECTIVES The performance of prediction models tends to deteriorate over time. The purpose of this study was to update the Thoracoscore risk prediction model with recent data from the Epithor nationwide thoracic surgery database. METHODS From January 2016 to December 2017, a total of 56 279 patients were operated on for mediastinal, pleural, chest wall or lung disease. We used 3 recommended methods to update the Thoracoscore prediction model and then proceeded to develop a new risk model. Thirty-day hospital mortality included patients who died within the first 30 days of the operation and those who died later during the same hospital stay. RESULTS We compared the baseline patient…
QSAR Analysis of Hypoglycemic Agents Using the Topological Indices
2001
The molecular topology model and discriminant analysis have been applied to the prediction of some pharmacological properties of hypoglycemic drugs using multiple regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies performed on the selected prediction models confirmed the goodness of the fits. The method used for hypoglycemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and selection of new hypoglycemic agents, and we …
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 Comprehensive Check of Usle-Based Soil Loss Prediction Models at the Sparacia (South Italy) Site
2020
At first, in this paper a general definition of the event rainfall-runoff erosivity factor for the USLE-based models, REFe = (QR)b1(EI30)b2, in which QR is the event runoff coefficient, EI30 is the single-storm erosion index and b1 and b2 are coefficients, was introduced. The rainfall-runoff erosivity factors of the USLE (b1 = 0, b2 = 1), USLE-M (b1 = b2 = 1), USLE-MB (b1 ≠ 1, b2 = 1), USLE-MR (b1 = 1, b2 ≠ 1), USLE-MM (b1 = b2 ≠ 1) and USLE-M2 (b1 ≠ b2 ≠ 1) can be defined using REFe. Then, the different expressions of REFe were simultaneously tested against a dataset of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predict…
Geospatial modelling and map analysis allowed measuring regression of the upper limit of Posidonia oceanica seagrass meadows under human pressure
2018
Abstract Marine coastal ecosystems are facing structural and functional changes due to the increasing human footprint worldwide, and the assessment of their long-term changes becomes particularly challenging. Measures of change can be done by comparing the observed ecosystem status to a purposely defined reference condition. In this paper, a geospatial modelling approach based on 2D mapping and morphodynamic data was used to predict the natural position of the upper limit (i.e., the landward continuous front) of Posidonia oceanica seagrass meadows settled on soft bottom. This predictive model, formerly developed at the regional spatial scale, was here applied for the first time at the Medit…
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…
Importance of the Window Function Choice for the Predictive Modelling of Memristors
2021
Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here, we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absenc…
Practical thresholds to distinguish erosive and rill rainfall events
2019
Abstract In this paper, 1017 rainfall events from 2008 to 2017 are used to identify the rainfall threshold that produces upland erosion at the Masse (central Italy) and Sparacia (southern Italy) experimental stations. The rainfall events are classified into three classes: non-erosive, interrill-only and rill. The threshold values for separating as correctly as possible the erosive rains (case I) and the rill rains (case II) are derived solely from the hyetograph. Each threshold value is obtained by imposing that the long-term erosivity of the events above the threshold is equal to the long-term erosivity of all erosive events (case I) or only rill events (case II). The performances of selec…
Towards the improvement of food flavour analysis: Modelling chemical and sensory data and expert knowledge integration
2019
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