Feedback Control for Personalized Medicine

Herausgegeben:Hernandez-Vargas, Esteban A.

• Broschiertes Buch

Produktbeschreibung

Feedback Control for Personalized Medicine provides ideas on ongoing efforts and obstacles by members of the control engineering community in different biological and medical applications. In addition, the book presents key challenges, insights, tools and theoretical developments that arise from personalized medicine, along with medical concepts that are explained by engineers to help non-experts follow research topics. Several clinical trials have tried to find therapeutic approaches to achieve eradication or at least lifelong, therapy-free, host control of the infection. This has been performed integrating clinical observations, empirical knowledge and information from medical tests to treat patients.

As this "trial and error? approach is becoming more challenging and unfeasible by the steep increase in the number of different pieces of information and the complexity of large datasets, a systematic and tractable approach that integrates a variety of biological and medical research data into mathematical models and computational algorithms is crucial to harness knowledge and to develop new therapies towards personalized medicine.

Produktdetails

• Verlag: Academic Press / Elsevier Science & Technology
• Artikelnr. des Verlages: C2020-0-03670-4
• Seitenzahl: 246
• Erscheinungstermin: 25. April 2022
• Englisch
• Abmessung: 151mm x 227mm x 21mm
• Gewicht: 410g
• ISBN-13: 9780323901710
• ISBN-10: 0323901719
• Artikelnr.: 62762758

Autorenporträt

Esteban Abelardo Hernandez Vargas. Associate Professor, Institute of Mathematics, UNAM, Mexico

Inhaltsangabe

1. Introduction to Control Theory Towards Personalized Medicine
2. Control schemes for Personalizing Therapies
3. Input-output approaches for personalized drug dosing of antibiotics
4. Safe glycemia regulation considering parameter variations under the offset-free MPC with pulse inputs scheme
5. Glycemia regulation using Neural Networks
6. Personalizing therapeutic treatments in Influenza Infection
7. Polynomial state estimation in infectious diseases
8. Sliding mode control theory interprets elite control of HIV
9. A stochastic model for Hepatitis C viral infection dynamics with the innate immune response
10. First approach to impulsive nonlinear MPC with application to Oncolytic Virus Therapy
11. Is the isolated heart a relaxation oscillator?