Handbook of Optimization in Medicine (eBook, PDF)

Redaktion: Pardalos, Panos M.; Romeijn, H. Edwin

• Format: PDF

Produktbeschreibung

Handbook of Optimization in Medicine is devoted to examining the dramatic increase in the application of effective optimization techniques to the delivery of health care. The articles, written by experts from the areas of operations research, computer science, and medicine, focus on models and algorithms that have led to more efficient and sophisticated treatments of patients.

Topics covered include: optimization in medical imaging, classification and data mining with medical applications, treatment of epilepsy and other brain disorders, treatment of head-and-neck, prostate, and other cancers using conventional conformal and intensity-modulated radiation therapy as well as proton therapy, treatment selection for breast cancer based on new classification schemes, optimization for the genome project, optimal timing of organ transplants.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 442
• Erscheinungstermin: 8. Juli 2014
• Englisch
• ISBN-13: 9780387097701
• Artikelnr.: 43729110

Inhaltsangabe

Optimizing Organ Allocation and Acceptance.- Can we Do Better? Optimization Models for Breast Cancer Screening.- Optimization Models and Computational Approaches for Three-dimensional Conformal Radiation Treatment Planning.- Continuous Optimization of Beamlet Intensities for Intensity Modulated Photon and Proton Radiotherapy.- Multicriteria Optimization in Intensity Modulated Rediotherapy Planning.- Algorithms for Sequencing Multileaf Collimators.- Image Registration and Segmentation Based on Energy Minimization.- Optimization Techniques for Date Representions with Biomedical Applications.- Algorithms for Genomics Analysis.- Optimization and Data Mining in Epilepsy Research: A Review and Prospective.- Mathematical Programming Approaches for the Analysis of Microarray Data.- Classification and Disease Prediction Via Mathematical Programming.