Search results for "Predictive Model"

Contextes spatiaux et transformation du système de peuplement: approche comparative et prédictive

2011

We propose a method to identify and simulate settling choices Roman rural settlements using predictive modeling, based on the method developed in the 1990s by F.-P. Tourneux within the Archaeomedes project to characterize and compare the environmental contexts of Roman rural settlements in several areas of southern France. We have developped the model for three regions with very different topographical conditions : The Vaunage region (Languedoc, France), the Argens-Maures region (Provence, France) and Zuid-Limburg (Netherlands).

Innovative tools to diagnose the impact of land use practices on soil microbial communities

2018

International audience; Preservation and sustainable use of soil biological communities represent major challenges in the current agroecological context. Indeed, most of soil ecosystem services results from biological functions particularly driven by taxonomic and functional assemblages of microbiological communities (i.e. nutrient cycling, soil aggregation, depollution, etc.). Consequently, soil microbial communities are logical candidates as effective indicators of soil quality and sustainability. But, good biological indicators must be associated with references that encompass an operating range of measured values that allow performing the desired diagnosis. Even if numerous studies have…

Forecasts on the development of hydrogen refuelling infrastructures in Portugal

2021

In Portugal, the transition to new forms of mobility has begun in recent years, but there are still obstacles to overcome. Currently, hybrid vehicles (PHEVs) are the most widespread and accepted by the community and that is probably due to range anxiety, having in fact the possibility of double charging (both through the thermal engine and the electric battery). Furthermore, it must be considered that in addition to electric vehicles, another valid alternative to mobility in the near future is the hydrogen vehicles one. These appear to be even more sustainable from the point of view of air emissions, but on the other hand the costs for the production of hydrogen are still too high. Then, th…

Anemia management in end stage renal disease patients undergoing dialysis: a comprehensive approach through machine learning techniques and mathemati…

2016

Kidney impairment has global consequences in the organism homeostasis and a disorder like Chronic Kidney Disease (CKD) might eventually exacerbates into End Stage Renal Disease (ESRD) where a complete renal replacement therapy like dialysis is necessary. Dialysis partially reintegrates the blood ltration process; however, even when it is associated to a pharmacological therapy, this is not su fficient to completely replace the renal endocrine role and causes the development of common complications, like CKD secondary anemia (CKD-anemia) The availability of exogenous Erythropoiesis Stimulating Agents (ESA, synthetic molecules with similar structure and same mechanism of action as human eryth…

Child abuse/neglect risk assessment under field practice conditions: Tests of external and temporal validity and comparison with heart disease predic…

2015

AbstractObjectives (1) Identify validation design and accuracy assessment standards for medical prognostic models applicable to evaluation of child abuse/neglect (CA/N) risk assessment models. (2) Assess the accuracy of the California Family Risk Assessment (CFRA) in predicting CA/N using the foregoing standards. (3) Compare the prediction accuracy of the CFRA with the prediction accuracy of coronary heart disease (CHD) prediction models. Questions addressed (1) What validation design and accuracy assessment standards are used to evaluate medical prognostic models? (2) What is the evidence for the accuracy of the CFRA using those standards? (3) How does the accuracy of the CFRA in predictin…

Opportunities for the Use of Business Data Analysis Technologies

2016

Abstract The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.

Environmental drivers of lake profundal macroinvertebrate community variation : implications for bioassessment

2011

Application of an interspecific competition model to predict the growth of Aeromonas hydrophyla on fish surfaces during refrigerated storage (Anwendu…

2007

The growth of Aeromonas hydrophila and the aerobic mesophilic plate count (APC) on gilthead seabream surfaces was evaluated during refrigerated storage (21 days). The related growth curves were compared with those obtained by a conventional third order predictive model obtaining a low agreement between observed and predicted data (Root Mean Squared Error = 1.77 for Aeromonas hydrophila and 0.64 for APC).The Lotka-Volterra interspecific competition model was used in order to calculate the degree of interaction between the two bacterial populations (beta_{Ah/APC} and beta_{APC/Ah}, respectively, the interspecific competition coefficients of APC on Aeromonas hydrophila and vice-versa). Afterwa…

Estimating “land use heritage” to model changes in archaeological settlement patterns

2016

International audience; In this paper, we present a method to calculate a “land use heritage map” based on the concept of “memory of landscape”. Such a map can be seen as one variable among others influencing site location preference, and can be used as input for predictive models. The computed values equate to an index of long-term land use intensity. We will first discuss the method used for creating the land use heritage map, for which kernel density estimates are used.We will then present the use of these land use heritage maps for site location analysis in two study areas in SE France. Earlier analyses showed that the influence of the natural environment on settlement location choice i…

Predicting survival after transarterial chemoembolization for hepatocellular carcinoma using a neural network: A Pilot Study.

2019

BACKGROUND AND AIMS Deciding when to repeat and when to stop transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) can be difficult even for experienced investigators. Our aim was to develop a survival prediction model for such patients undergoing TACE using novel machine learning algorithms and to compare it to conventional prediction scores, ART, ABCR and SNACOR. METHODS For this retrospective analysis, 282 patients who underwent TACE for HCC at our tertiary referral centre between January 2005 and December 2017 were included in the final analysis. We built an artificial neural network (ANN) including all parameters used by the aforementioned risk scores a…