Method for predicting lung cancer using deep learning techniques, involves developing a deep learning based lung cancer detection method using Convolutional Neural Network (CNN) architecture for fast and accurate
	KALAISELVI B; HABIBA U H; VIJAYAN T; REDDY K L; JAGADEESH K
	2023-10-16
专利权人	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
申请日期	2023-10-16
专利号	IN202341069665-A
成果简介	NOVELTY - The method involves developing a deep learning based lung cancer detection method using Convolutional Neural Network (CNN) architecture for fast and accurate. The early stage of lung cancer is found, and the accuracy levels and various performance metrics are explored. Multiple deep learning models for medical image analysis arn developed to help classify lung cancer. An evolutionary algorithm is used to optimise the classification of lung cancer with CNNs. USE - Method for predicting lung cancer using deep learning techniques. ADVANTAGE - The method enables developing an artificial intelligence (AI) based/machine learning or deep learning model to reduce time and improve lung cancer detection accuracy. The proposed deep learning-assisted CNN based model yields 99% accuracy for lung cancer detection representing early-stage of identification.
IPC 分类号	G06N-020/00 ; G06N-003/0464 ; G06N-003/08 ; G06T-007/00 ; G16H-030/40 ; G16H-050/20
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/19846
专题	中国科学院新疆生态与地理研究所
作者单位	BHARATH HIGHER EDUCATION & RES INST (BHAR-Non-standard)
推荐引用方式 GB/T 7714	KALAISELVI B,HABIBA U H,VIJAYAN T,et al. Method for predicting lung cancer using deep learning techniques, involves developing a deep learning based lung cancer detection method using Convolutional Neural Network (CNN) architecture for fast and accurate. IN202341069665-A[P]. 2023.

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