Description
Book SynopsisThe potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primarily clinicians - who present the results of their state-of-the-art work with ANNs as applied to nearly all major areas of cancer for diagnosis, prognosis, and management of the disease.
The book introduces the theory of neural networks and the method of their application in oncology. It is not an exercise in ANN research, but the presentation of a new technique for diagnosing and determining the treatment of cancers. The authors have included almost all cancers for which there exist ANN applications. When the data available is ill-defined and the development of an algorithmic solution difficult, neural networks provide a non-linear appro
Table of ContentsIntroduction to Artificial Networks and Their Use in Cancer Diagnosis, Prognosis, and Patient Management. Analysis of Molecular Prognostic Factors in Breast Cancer by Artificial Neural Networks. Artificial Neural Approach to Analysing the Prognostic Significance of DNA Ploidy and Cell Cycle Distribution of Breast Cancer Aspirate Cells. Neural Networks for the Estimation of Prognosis in Lung Cancer. The Use of a Genetic Algorithm Neural Network (GANN) for Prognosis in Surgically Treated Non-Small Cell Lung Cancer (NSCLC). The Use of Machine Learning in Screening for Oral Cancer. Outcome Prediction of Oesophago-Gastric Cancer Using Neural Analysis of Pre- and Post-Operative Parameters. Artificial Neural Networks in Urologic Oncology. Neural Networks in Urologic Oncology. Comparison of a Neural Network with High Sensitivity and Specificity to Free/Total Serum PSA for Diagnosing Prostate Cancer in Men with PSA. Artificial Neural Networks and Prognosis in Prostate Cancer. Comparison Between Urologists and Artificial Neural Networks in Bladder Cancer Outcome Prediction. A Probabilistic Neural Network Framework for Detection of Malignant Melanoma.
