1,196 search results for “predictive modelling” in the Public website
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Case studies in archaeological predictive modelling
ASLU 14
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Predictive Modelling for Archaeological Heritage Management
A research agenda
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Strategic research into and development of best practice for, predictive modelling on behalf of Dutch Cultural Resource Management
Are predictive archaeological maps a reliable tool to play an important role in the spatial planning? One of the goals of this project was to develop best practices for the production and application of the models.
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Better Predictions when Models are Wrong or Underspecified
Promotor: P.D. Grünwald
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Postdoc Computational Modeling for Drug Safety Prediction
Science, Leiden Academic Centre for Drug Research (LACDR)
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Proteochemometric modelling coupled to in silico target prediction
An integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules.
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Development of Quantitative Nanostructure Activity Relationship (QNAR) Models Predicting the Toxicity of Metal-based Nanoparticles to Aquatic Species
Describe and identify what dosimetry parameters are of importance to interpret dose-response relationships (eg., mortality, sub-lethal, growth or reproduction inhabitation, DNA damage and reactive oxygen species, etc. ) for metal-based nanoparticles? How to develop quantitative models that enable to…
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From Descriptive to Predictive Pharmacology in Children using Semi-Physiological population modelling
An integrated approach of physiological concepts, advanced statistical approaches and large clinical datasets.
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Systems pharmacokinetic models to the prediction of local CNS drug concentrations in human
Clinical development of drugs for central nervous system (CNS) disorders has been particularly challenging and still suffers from high attrition rates.
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Gerard van Westen: 'Our model predicts what candidate drugs do in your body'
He’s a fast and animated speaker, which is only logical because Gerard van Westen is driving an express train. His destination? A virtual human, consisting of algorithms that predict what an administered substance will do in the body. The train is already a long way down the line and the pharmaceutical…
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Prediction of the potency of mammalian cyclooxygenase inhibitors with ensemble proteochemometric modeling
Source: J Cheminform, Volume 7, Issue 1 (2015)
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Personalised medicine for multiple outcomes: methods and application
The main objective of this thesis was to develop clinically relevant survival models for patients with high-grade soft tissue sarcoma of the extremities, in particular the development and validation of prediction models for use in clinical practice.
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Archaeological Prediction and Risk Management
Alternatives to current practice
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Prediction of spatial-temporal brain drug distribution with a novel mathematical model
A novel mathematical model describes spatial-temporal drug distribution within one or more brain units, which are cubic representations of a piece of brain tissue with brain capillaries at the edges.
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Data-driven donation strategies: understanding and predicting blood donor deferral
The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels.
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Predictive value of semi-physiological models for clearance of renally excreted drugs across the paediatric age range
The kidneys play a major role in the elimination of drugs. In children, the exact age-related physiological changes underlying kidney function remain largely unknown.
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Deconstructing stability. Modelling changing environmental conditions and man-land relations in the Pleistocene landscape of Twente (2850 - 12
The project Deconstructing Stability aims to improve reconstructions of late prehistoric landscapes and predictive models for the purpose of archaeological heritage management.
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Predictive Pharmacology
Prof. Elizabeth de Lange is concerned with the allocation of resources for the conduct of science towards the goal of best serving the public interest. Also, while she underscores that there is still the need for using animals in drug research, she is concerned about this use, and advocates the use…
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From descriptive to predictive pharmacology in children using semi-physiological population modelling: application to hepatic metabolism
Clearance is the most important pharmacokinetic parameter for drug dose selection. Pharmacokinetic information is typically first available in the adult population, and in general only limited pharmacokinetic data are available in children when drugs enter into the market. It is therefore of the utmost…
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Predictive pharmacology
The aim of this research area is to be able to predict human drug response on the basis of mathematical models that are developed using preclinical experiments and prior knowledge.
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CIMPLO – Maintenance prediction for industries
Researchers of the Leiden Institute of Advanced Computer Science (LIACS) have started a 4 year project on developing a system that sends out automatic alerts when components from engines are showing first signs of fatigue.
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Mathematical model predicts drug concentration in the brain
Do medicines arrive in the right amount at the right spot in our brain? By making a model that depicts our brain in small 'brain blocks', Esmée Vendel tries to find an answer to this question. Her new, mathematical model predicts the concentration of medicines in the brain over time and space. Vendel…
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Data Driven Modeling & Optimization of Industrial Processes
Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.
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New model predicts ‘yoyo’ orbits around black holes
Stars orbit black holes while jumping up and down. This is the prediction of a theoretical model developed by Leiden physicist Satish Kumar Saravanan, based on Einstein’s theory of relativity. He defends his PhD thesis on July 7th.
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Predicting dementia
In the future, physicians may be able to identify dementia much earlier than they can today because a computer algorithm will be able to predict from brain scans how our memory is going to develop.
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Predicting the future: Predictive control for astronomical adaptive optics
The field of exoplanet research is rapidly advancing through the development of new technology, observing techniques, and post-processing methods.
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Novel system-inspired model-based quantum machine learning algorithm for prediction and generation of High-Energy Physics data
Assistant Professor Vedran Dunjko and his team received a gift from Google to support their quantum research. The research focuses on whether quantum computers can provide new ways of understanding the mysteries of high-energy physics.
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Prediction of binding kinetics
Supervisor: Gerard van Westen
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Biotic ligand models
Description of Biotic ligand models: making an inventory of available models & assessment of the variability of the predicted HC5 using the BLMs in different Dutch water types (2005 - 2007)
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Mathematical modelling of advanced herbal extraction
Can the (industrial) herbal extraction process be mathematically described and can this model be used to optimize the extraction in terms of quality and economical parameters?
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Terrorism Experts’ Predictions Regarding the Effects of the COVID-19 Pandemic on the Activities of Violent Non-State Actors
In this article, Yannick Veilleux-Lepage and Tommy van Steen, assistant professors at the Institute of Security and Global Affairs, discuss the degree of consensus within the field of terrorism studies regarding the impact of the COVID-19 pandemic on the activities of violent non-state actors.
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Towards predictive cardiovascular safety: a systems pharmacology approach
Promotores: Prof.dr. M. Danhof, Prof.dr. D.R. Stanski
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Advanced in vitro models for studying drug induced toxicity
Promotor: Prof.dr. B. van de Water, Co-promotor: L.S. Price
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Mathematical modelling of adverse outcome pathways
In this project, we aim to develop mathematical models to mechanistically and quantitatively predict the dynamics of cellular stress pathway activation and its relation with toxic effects when cells are exposed to various toxicants.
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Robust rules for prediction and description.
In this work, we attempt to answer the question:
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Inhibitor Selectivity: Profiling and Prediction
Less than 1 in 10 drug candidates that enter phase 1 clinical trials actually gets approved for human use.
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secretion in predicting renal clearance in children using population pharmacokinetic and physiology based pharmacokinetic modeling approaches
In this thesis population pharmacokinetic and physiologically-based pharmacokinetic (PBPK) approaches were applied to investigate the influence of glomerular filtration (GF) and active tubular secretion (ATS) on renal clearance in children.
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Unraveling temporal processes using probabilistic graphical models
Real-life processes are characterized by dynamics involving time. Examples are walking, sleeping, disease progress in medical treatment, and events in a workflow.
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AI in Neuroscience: Development of Methods to make Personalized Predictions for Migraine and Stroke from E-Health Sensor Data
The research of this PhD project can be subdivided into two main disease areas: migraine and stroke. For both we will be investigating how artificial intelligence (AI) and machine learning (ML) techniques can be used to study these afflictions, their (early) detection, and their potential treatment.
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New vegetation models can improve climate change predictions
A new study in Nature Plants has explored the most important organising principles that control vegetation behaviour. The insights from this study can be used to improve predictions on climate change. Leiden scientists Peter van Bodegom and Nadia Soudzilovskaia participated in the study.
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XAIPRE - Explainable AI For Predictive Maintenance
The project XAIPre (pronounce “Xyper”) aims to develop predictive maintenance system for the maritime industry using sensor technology and artificial intelligence. The project aims at developing Explainable Predictive Maintenance (XPdM) algorithms that do not only provide the engineers with a prediction…
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Optimally weighted ensembles of surrogate models for sequential parameter optimization
It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.
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Advances in GPCR Modeling Evaluated by the GPCR Dock 2013 Assessment: Meeting New Challenges
Source: Structure , Volume 22, Issue 8, pp. 1120-1139 (2014)
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Animal models for cutaneous vaccine delivery
Main challenges in skin vaccination are overcoming the stratum corneum (SC) barrier and targeting the antigen presenting cells (APC) in the epidermis and the dermis.
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Prediction of human (CNS) target site concentrations in health and disease
Prediction of human (CNS) target site concentrations in health and disease In the vision of Prof. de Lange we will only be able to predict human (central nervous system, CNS) target site concentrations and effects if we perform systematic, condition-dependent, integrative, and strictly quantitative…
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Prediction Sets via Parametric and Nonparametric Bayes: with Applications in Pharmaceutical Industry
This thesis consists of five chapters on how to construct prediction sets for different types of data and models in a parametric or nonparametric Bayesian paradigm.
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Prediction of human gut (colon cancer) target site concentrations and PKPD relationships
The advanced insights obtained for the CNS PBPK model development are currently used to develop advanced mathematical models for drug distribution prediction in other body tissues protected by barriers, such as the gut. The gut PBPK model will be linked to drug effects for treatment of colon cancer.
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Prediction of brain target site concentrations on the basis of CSF PK: impact of mechanisms of blood-to-brain transport and within brain distribution
Promotor: Prof.dr. M. Danhof, Co-promotor: E.C.M. de Lange
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Pharmacology based toxicity assessment: towards quantitative risk prediction in humans
Promotor: Prof.dr. M. Danhof, Co-promotor: O.E. Della Pasqua
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Quantitative modelling of the response of earthworms to metals
Promotor: Prof.dr. W.J.G.M. Peijnenburg, Co-promotor: Dr. ing. M.G. Vijver