MINIMIZING BREAST CANCER SYMPTOMATOLOGY IN RECURRENCE PREDICTION USING ARTIFICIAL NEURAL NETWORKS

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" MINIMIZING BREAST CANCER SYMPTOMATOLOGY IN RECURRENCE PREDICTION USING ARTIFICIAL NEURAL NETWORKS "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	150620
Doc. No	:	ET22412
Main Entry	:	Anna Besse
Title Proper	:	MINIMIZING BREAST CANCER SYMPTOMATOLOGY IN RECURRENCE PREDICTION USING ARTIFICIAL NEURAL NETWORKS
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	In the process of dagnosing and treating breast cancer patients, doctors are presentedwith a wide array of symptoms and varymg degrees of complication. Rased on all theinformation available for each patient, it is the doctor's responsibdity to make life or deathdecisions about that patient's care. Some examples of the types of decisions made are: howmuch chemotherapy should the patient have, should he/she have addtional concurrenttherapies, and whether the patient should have post-chemotherapy treatment or not. Often amajor part of the doctors' decision process involves estimation of the likelihood of relapsebased on the current treatment being administered. If the patient has a high likelihood ofrelapse they will have to go through more and stronger levels of treatment in order to gve....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL45628.pdf
Title and statement of responsibility and	:	MINIMIZING BREAST CANCER SYMPTOMATOLOGY IN RECURRENCE PREDICTION USING ARTIFICIAL NEURAL NETWORKS [Thesis]