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SYSTEM FOR DETECTION OF LEUKEMIA USING HIDDEN MARKOV MODEL AND ADAPTIVE NEURO FUZZY INFERENCE SYSTEM

机译:隐马尔可夫模型和自适应神经模糊推理系统的白血病检测系统

摘要

Disease diagnosis is an indispensable task where the human and computer combine to achieve optimal results by stabilizing the knowledge of Healthcare specialist in correlating the problems. Cancer is a major cause for human death which badly needs diagnosis at an earlier stage for further better treatments. For that data mining techniques are used in this work. The various methods such as EICA (Enhanced Independent Component Analysis), GPSO (Geometric Particle Swarm Optimization), AWFCM-BEA (Adaptive Weighted Fuzzy Clustering C-Means), HMM ANFIS (Hidden Markov Model -Adaptive Neuro Fuzzy Inference System) are used for classifying the blood samples. Simulation works are carried out using MATLAB 8.1.
机译:疾病诊断是必不可少的任务,其中人和计算机可以通过稳定医护人员在相关问题上的知识来结合以达到最佳结果。癌症是导致人类死亡的主要原因,因此迫切需要在早期进行诊断以寻求更好的治疗方法。为此,在这项工作中使用了数据挖掘技术。 EICA(增强的独立分量分析),GPSO(几何粒子群优化),AWFCM-BEA(自适应加权模糊聚类C均值),HMM ANFIS(隐马尔可夫模型-自适应神经模糊推理系统)等各种方法用于对血液样本进行分类。仿真工作是使用MATLAB 8.1进行的。

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