Modelling lymphoma therapy and outcome

DOI10.1007/S11538-013-9925-3zbMath1297.92044OpenAlexW2032449612WikidataQ41957184 ScholiaQ41957184MaRDI QIDQ458674

Katja Roesch, Dirk Hasenclever, Markus Scholz

Publication date: 8 October 2014

Published in: Bulletin of Mathematical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11538-013-9925-3

zbMATH Keywords

survival analysischemotherapyimmune systemlymphomamaximum-entropy distributions

Mathematics Subject Classification ID

Medical applications (general) (92C50)

Related Items (7)

Identifying and characterising the impact of excitability in a mathematical model of tumour-immune interactions ⋮ An optimization method for treating solid tumors with combined therapy using the great deluge algorithm ⋮ An immune system-tumour interactions model with discrete time delay: model analysis and validation ⋮ Combined therapy for treating solid tumors with chemotherapy and angiogenic inhibitors ⋮ Mathematics + Cancer: An Undergraduate "Bridge" Course in Applied Mathematics ⋮ Therapy strategy in tumour cells and immune system interaction mathematical model ⋮ Optimizing treatment combination for lymphoma using an optimization heuristic

Uses Software

• BRENT

Cites Work

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• Numerical mathematics. I.
• Modeling immunotherapy of the tumor -- immune interaction
• Nonlinear dynamics of immunogenic tumors: Parameter estimation and global bifurcation analysis
• A mathematical model of tumor-immune evasion and siRNA treatment
• What can be learned from a chaotic cancer model?
• Modelling human granulopoiesis under poly-chemotherapy with G-CSF support
• Behavior of tumors under nonstationary therapy
• Mixed immunotherapy and chemotherapy of tumors: modeling, applications and biological interpretations
• A mathematical model of the treatment and survival of patients with high-grade brain tumours
• A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach
• Information Theory and Statistical Mechanics
• Evolutionary Computation for Modeling and Optimization
• Descartes' Rule of Signs Revisited
• Dynamic response of cancer under the influence of immunological activity and therapy

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