Mats Jirstrand
Showing 96 publications
Probabilistic analysis of tumor growth inhibition models to Support trial design
Effects on district heating networks by introducing demand side economic model predictive control
Model-based assessment of combination therapies - ranking of radiosensitizing agents in oncology
Model-based Prediction of Progression-Free Survival for Combination Therapies in Oncology
Identification of metabotypes in complex biological data using tensor decomposition
Model-based prediction of progression-free survival for combination therapies in oncology
SKA Science Data Challenge 2: analysis and results
A Model Based Approach for Translation in Oncology - From Xenografts to RECIST
Optimized scaling of translational factors in oncology: from xenografts to RECIST
Identifying metabotypes from tensor data
Exposure-response modeling improves selection of radiation and radiosensitizer combinations
Population Modeling of Toxicological Combination Effects
Identifying metabotypes from complex biological data using PARAFAC
An Integrative Approach for Improved Assessment of Cardiovascular Safety Data
S-RASTER: contraction clustering for evolving data streams
Reinforcement Learning Informed by Optimal Control
Architecture-Aware Bayesian Optimization for Neural Network Tuning
Dose-Response-Time Data Analysis: An Underexploited Trinity
Federated Learning of Deep Neural Decision Forests
Parameter Estimation for Nonlinear Mixed Effects Models Implemented in Mathematica
Challenge model of TNFα turnover at varying LPS and drug provocations
On Chow-Liu Forest Based Regularization of Deep Belief Networks
Modeling long-term tumor growth and kill after combinations of radiation and radiosensitizing agents
Bayesian hierarchical model of oscillatory cortisol response during drug intervention
Model-based evaluation of radiation and radiosensitizing agents in oncology
A Performance Evaluation of Federated Learning Algorithms
Reinforcement learning in real-time geometry assurance
Analysis of Engineering Change Requests Using Markov Chains
Modeling of radiation therapy and radiosensitizing agents in tumor xenografts
Extending existing structural identifiability analysis methods to mixed-effects models
Evaluation and translation of combination therapies in oncology – A quantitative approach
Functional Federated Learning in Erlang
Tumor Static Concentration Curves in Combination Therapy
Assessment of cardiotoxic effects from ion channel assay data
Design Analytics is the Answer, But What Questions Would Product Developers Like to Have Answered?
Purely Functional Federated Learning in Erlang
Towards Big-Data Analysis of Deviation and Error Reports in Product Development Projects
Dose-response-time modelling: Second-generation turnover model with integral feedback control
Bile canalicular dynamics in hepatocyte sandwich cultures
Structural Identifiability in Mixed-Effects Models: Two different approaches
Two approaches to study structural identifiability analysis in mixed-effects models
Dose-response-time modelling - Second generation turnover model with integral feedback control
Structural Identifiability in mixed-effects models
Comparison of approaches for parameter identifiability analysis of biological systems.
Kinetic models in industrial biotechnology - Improving cell factory performance
Bridging the gaps in systems biology
Structural Identifiability Analysis of Large Models of Dynamical Systems
Toward Quantifying the Thymic Dysfunctional State in Mouse Models of Inflammatory Bowel Disease
Optimal posterior density approximation for bearings-only tracking
An Efficient Method for Structural Identiability Analysis of Large Dynamic Systems
Minimal output sets for identifiability
A Method for Zooming of Nonlinear Models of Biochemical Systems
Optimal parameterization of posterior densities using homotopy
Modeling the Effect of Kv1.5 Block on the Canine Action Potential
Zooming of states and parameters using a lumping approach including back-translation
Biochemical Modeling with Systems Biology Graphical Notation
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