Study of Applications of Artificial Neural Networks

Kaleem Ullah Moon
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Abstract

This study is related to the different methods of identification of artificial neural networks. These techniques assess and detect lung cancer in the early stage of life, therefore, preventing lung disease. Growth in lung cancer is Pakistan's principal cause of death, so early identification of lung disease is crucial. The position and expectation of growth of lung cancer is guided by the pre-treatment plan in which sections, smoothing, and improvement measures were prepared which includes procedures based on pictures and steps. Lung malignancy was linked to the proper model of the false neural system and paces of the endurance of patients with lung disease were also determined. The role of artificial neural systems in the medical profession is significant Nowadays most ailment treatment strategies are prepared to upgrade the yield display with the aid of man-made brainpower. The artificial neural network model is useful in lung cancerous growth disorder because lung type of cancer can be detected. The main aim of this paper is to study the different methods of artificial neural network techniques used to detect, assess, and treat patients with lung cancer. 
人工神经网络的应用研究
本研究涉及人工神经网络识别的不同方法。这些技术在生命的早期阶段评估和检测肺癌,从而预防肺部疾病。肺癌的增长是巴基斯坦的主要死亡原因,因此早期发现肺部疾病至关重要。肺癌生长的位置和预期以治疗前计划为指导,治疗前计划中制定了切片、平滑和改善措施,包括基于图片和步骤的程序。肺部恶性肿瘤与假神经系统的适当模型和肺部疾病患者的耐力速度有关。人工神经系统在医学领域的作用是重要的,目前大多数疾病的治疗策略都是利用人工智能来提高产量。人工神经网络模型在肺癌生长障碍诊断中具有重要的应用价值。本文的主要目的是研究人工神经网络技术用于肺癌患者的检测、评估和治疗的不同方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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