Outcome Prediction in Cancer

This book is organized into 4 sections, each looking at the question of outcome prediction in cancer from a different angle. The first section describes the clinical problem and some of the predicaments that clinicians face in dealing with cancer. Amongst issues discussed in this section are the TNM staging, accepted methods for survival analysis and competing risks. The second section describes the biological and genetic markers and the rôle of bioinformatics. Understanding of the genetic and environmental basis of cancers will help in identifying high-risk populations and developing effective prevention and early detection strategies. The third section provides technical details of mathematical analysis behind survival prediction backed up by examples from various types of cancers. The fourth section describes a number of machine learning methods which have been applied to decision support in cancer. The final section describes how information is shared within the scientific and medical communities and with the general population using information technology and the World Wide Web. * Applications cover 8 types of cancer including brain, eye, mouth, head and neck, breast, lungs, colon and prostate * Include contributions from authors in 5 different disciplines * Provides a valuable educational tool for medical informatics

Produk Detail:

  • Author : Azzam F.G. Taktak
  • Publisher : Elsevier
  • Pages : 482 pages
  • ISBN : 9780080468037
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKOutcome Prediction in Cancer

Outcome Prediction in Cancer

Outcome Prediction in Cancer
  • Author : Azzam F.G. Taktak,Anthony C. Fisher
  • Publisher : Elsevier
  • Release : 28 November 2006
GET THIS BOOKOutcome Prediction in Cancer

This book is organized into 4 sections, each looking at the question of outcome prediction in cancer from a different angle. The first section describes the clinical problem and some of the predicaments that clinicians face in dealing with cancer. Amongst issues discussed in this section are the TNM staging, accepted methods for survival analysis and competing risks. The second section describes the biological and genetic markers and the rôle of bioinformatics. Understanding of the genetic and environmental basis of

Comprehensive Evaluation Composite Gene Features in Cancer Outcome Prediction

Comprehensive Evaluation Composite Gene Features in Cancer Outcome Prediction
  • Author : Dezhi Hou
  • Publisher : Unknown Publisher
  • Release : 21 June 2021
GET THIS BOOKComprehensive Evaluation Composite Gene Features in Cancer Outcome Prediction

There have been extensive studies of classification and prediction of cancer outcome with composite gene features that combine functionally related genes together as a single feature to improve the classification and prediction accuracy. Various algorithms have been proposed for feature extraction, feature activity inference, and feature selection, which all claim to improve the prediction accuracy. However, due to the limited test data sets used by each independent study, inconsistent test procedures, and conflicting results, it is difficult to obtain a

Outcome Prediction in Head and Neck Cancer Patients Using Machine Learning Methods

Outcome Prediction in Head and Neck Cancer Patients Using Machine Learning Methods
  • Author : David John Dellsperger,University of Iowa. College of Engineering. Biomedical Engineering
  • Publisher : Unknown Publisher
  • Release : 21 June 2021
GET THIS BOOKOutcome Prediction in Head and Neck Cancer Patients Using Machine Learning Methods

Head and Neck cancers account for approximately 3.2% of the estimated 1,660,290 new cancer cases for the year 2013 and roughly 1.9% of cancer-related deaths in 2013. In this research, machine learning techniques were employed to predict outcome in cancer patients supporting more objective assessment of the treatments, including surgery, radiation therapy, or chemotherapy. Selection of features capable of distinguishing between the possible outcomes was accomplished by using a highly selective cohort of 61 patients with similar treatment and location of the primary tumor. An accuracy

Prognostic Value of Histology and Lymph Node Status in Bilharziasis-Bladder Cancer: Outcome Prediction Using Neural Networks

Prognostic Value of Histology and Lymph Node Status in Bilharziasis-Bladder Cancer: Outcome Prediction Using Neural Networks
  • Author : Anonim
  • Publisher : Unknown Publisher
  • Release : 21 June 2021
GET THIS BOOKPrognostic Value of Histology and Lymph Node Status in Bilharziasis-Bladder Cancer: Outcome Prediction Using Neural Networks

In this paper, the evaluation of two features in predicting the outcomes of patients with bilharziasis bladder cancer has been investigated using an RBF neural network. Prior to prediction, the feature subsets were extracted from the whole set of features for the purpose of providing a high performance of the network. Throughout the analysis of the prognostic feature combinations, two features, histological type and lymph node status, have been identified as the important indicators for outcome prediction of this type

Advances in Computer and Information Sciences and Engineering

Advances in Computer and Information Sciences and Engineering
  • Author : Tarek Sobh
  • Publisher : Springer Science & Business Media
  • Release : 15 August 2008
GET THIS BOOKAdvances in Computer and Information Sciences and Engineering

Advances in Computer and Information Sciences and Engineering includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Computer Science, Software Engineering, Computer Engineering, and Systems Engineering and Sciences. Advances in Computer and Information Sciences and Engineering includes selected papers from the conference proceedings of the International Conference on Systems, Computing Sciences and Software Engineering (SCSS 2007) which was part of the International Joint Conferences on Computer, Information and Systems Sciences and Engineering (

Comparison of Diverse Genomic Data for Outcome Prediction in Cancer

Comparison of Diverse Genomic Data for Outcome Prediction in Cancer
  • Author : Hugo Gómez Rueda
  • Publisher : Unknown Publisher
  • Release : 21 June 2021
GET THIS BOOKComparison of Diverse Genomic Data for Outcome Prediction in Cancer

"Background. In cancer, large-scale technologies such as next-generation sequencing and microarrays have produced a wide number of genomic features such as DNA copy number alterations (CNA), mRNA expression (EXPR), microRNA expression (MIRNA), and DNA somatic mutations (MUT), among others. Several analyses of a specific type of these genomic data have generated many prognostic biomarkers in many cancer types, and more frequently in breast cancer. However, it is uncertain which of these data is more powerful and whether the best data-type

Cancer Epidemiology

Cancer Epidemiology
  • Author : Mukesh Verma
  • Publisher : Humana Press
  • Release : 23 October 2008
GET THIS BOOKCancer Epidemiology

Population studies and epidemiology facilitate the discovery of genetic and environmental determinants of cancer and the development of new approaches to cancer control and prevention, therefore they play a central role in the creation of health policies. Cancer Epidemiology compiles areas of research which cover etiological factors or determinants that contribute to the development of cancer and describe the latest technologies in cancer epidemiology. In Volume 1, Host Susceptibility Factors, leading experts provide chapters on cancer incidence, prevalence, mortality and surveillance,

Gynecologic Cancer

Gynecologic Cancer
  • Author : William P. McGuire,Martin Gore,Michael A. Quinn,Gillian Thomas
  • Publisher : Churchill Livingstone
  • Release : 21 June 2021
GET THIS BOOKGynecologic Cancer

This brand-new reference provides multidisciplinary guidance on the biology, diagnosis, treatment, and supportive care of patients with cancers of the female reproductive tract. An international group of experts present sections on management controversies, complications of cancer treatment, surgical techniques, symptom management, and more.

Urologic Surgical Pathology

Urologic Surgical Pathology
  • Author : David G. Bostwick,John N. Eble
  • Publisher : Mosby Incorporated
  • Release : 21 June 1997
GET THIS BOOKUrologic Surgical Pathology

This comprehensive text covers the entire urinary tract and male reproductive system in one well-illustrated volume. The book uses an organ-system approach, with major sections devoted to kidney, ureter/bladder, prostate and testis. For each organ system, the authors address anatomy and histology, and then move on to discussions of pathology of congenital anomalies, inflammations, neoplasia, and other disorders. Clinicopathologic and radiographic-pathologic correlations are emphasized, making the book a true diagnostic decision-making guide. * A true diagnostic decision-making guide--with clear emphasis