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Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis

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BMC CANCER 2019年第1期19卷 464-464页

作者： Yu, Lingming Tao, Guangyu Zhu, Lei Wang, Gang Li, Ziming Yi, Jianding Chen, Qunhui Shanghai Jiao Tong Univ Affiliated Chest Hosp Shanghai Chest Hosp Dept Radiol 241 Huaihai West Rd Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Affiliated Chest Hosp Shanghai Chest Hosp Dept Pathol Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Affiliated Chest Hosp Shanghai Chest Hosp Ctr Stat Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Affiliated Chest Hosp Shanghai Chest Hosp Ctr Lung Tumor Clin Med Shanghai 200030 Peoples R China

PurposeTo explore imaging biomarkers that can be used for diagnosis and prediction of pathologic stage in non-small cell lung cancer (NSCLC) using multiple machine learning algorithms based on CT image feature *** with stage IA to IV NSCLC were included, and the whole dataset was divided into training and testing sets and an external validation set. To tackle imbalanced datasets in NSCLC, we generated a new dataset and achieved equilibrium of class distribution by using SMOTE algorithm. The datasets were randomly split up into a training/testing set. We calculated the importance value of CT image features by means of mean decrease gini impurity generated by random forest algorithm and selected optimal features according to feature importance (mean decrease gini impurity >0.005). The performance of prediction model in training and testing sets were evaluated from the perspectives of classification accuracy, average precision (AP) score and precision-recall curve. The predictive accuracy of the model was externally validated using lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) samples from TCGA *** prediction model that incorporated nine image features exhibited a high classification accuracy, precision and recall scores in the training and testing sets. In the external validation, the predictive accuracy of the model in LUAD outperformed that in *** pathologic stage of patients with NSCLC can be accurately predicted based on CT image features, especially for LUAD. Our findings extend the application of machine learning algorithms in CT image feature prediction for pathologic staging and identify potential imaging biomarkers that can be used for diagnosis of pathologic stage in NSCLC patients.

关键词： Non-small cell lung cancer (NSCLC) Computed tomography (CT) Radiomics machine learning algorithm

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Implementation of machine learning algorithm on factors Effecting Divorce Rate

Implementation of Machine learning Algorithm on factors Effe...

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International Conference on Engineering and Emerging Technologies (ICEET)

作者： Sohail, Sana Aziz, Sadia Tahir, Faizan Haqqui, Sufyan Hussain, Ahsan Usman Inst Technol NEDUET Dept Elect Engn Karachi Pakistan Bahria Univ Dept Comp Sci Islamabad Pakistan Dadabhoy Inst Higher Educ Dept Comp Sci Karachi Pakistan

ISBN: (纸本)9781538632055

With the expanding number of marriages the quantity of detachment and separation are additionally expanding. The major factors that prompt separation can be numerous and there are numerous calculations in machine figuring out how to characterize the variables. The quantity of separation can be avoided and diminished on the off chance that we can have a decent information about the fundamental reasons and practices that can lead a connection to its end. In this paper we have taken a sample data set having some major attributes that causes divorce and comprehended it using 3 different classification algorithm and compared their outcomes. On the premise of their outcomes, we have concluded that which algorithm is more effective for the characterization of the data set in this application

关键词： machine learning algorithm Divorce Rate Artificial Intelligence Social Class

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Breast Cancer Diagnosis Using Adaptive Voting Ensemble machine learning algorithm

Breast Cancer Diagnosis Using Adaptive Voting Ensemble Machi...

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IEEMA IEEE Engineer Infinite Conference

作者： Khuriwal, Naresh Mishra, Nidhi Poornima Univ Jaipur Dept Comp Engn Jaipur Rajasthan India

ISBN: (纸本)9781538611388

According to Breast Cancer Institute (BCI), Breast Cancer is one of the most dangerous type of diseases that is very effective for women in the world. As per clinical expert detecting this cancer in its first stage helps in saving lives. As per *** offers individualized guides for more than 120 types of cancer and related hereditary syndromes. For detecting breast cancer mostly machine learning techniques are used. In this paper we proposed adaptive ensemble voting method for diagnosed breast cancer using Wisconsin Breast Cancer database. The aim of this work is to compare and explain how ANN and logistic algorithm provide better solution when its work with ensemble machine learning algorithms for diagnosing breast cancer even the variables are reduced. In this paper we used the Wisconsin Diagnosis Breast Cancer dataset. When compared to related work from the literature. It is shown that the ANN approach with logistic algorithm is achieved 98.50% accuracy from another machine learning algorithm.

关键词： Breast Cancer Neural Network Logistic machine learning algorithm WDBC Dataset

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Applications Research of machine learning algorithm in Translation System

Applications Research of Machine Learning Algorithm in Trans...

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2018 6th International Conference on machinery,Materials and Computing Technology(ICMMCT 2018)

作者： Lu Yang Da Chen Wenxue Wu School of Foreign Languages and Cultures Xihua University School of Science Xihua University

In recent years, machine translation has made outstanding achievements, but there are also the problems such as fuzzy rules, insufficient data and improper order in the machine translation practice, which makes it still unsatisfactory. machine learning can abstract learning features, and establish complex mapping relationship between input and output signals, and effectively improve the problems existing in the translation system. The concepts and common models of machine learning and deep learning are given in this paper. Based on the neural model, the paper analyses the rules, structure and models of machine translation system. According to the requirement of the translation system, this paper develops a translation system based on machine learning, and gives the design process of the pre-processing module, the coding module, the attention module and the decoding module. Practice has proved that the system has a good performance in translation performance.

关键词： machine learning algorithm Deep learning Translation system

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Chinese News Text Classification Based on machine learning algorithm

Chinese News Text Classification Based on Machine learning a...

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International Conference on Intelligent Human-machine Systems and Cybernetics

作者： Fang Miao Pu Zhang Libiao Jin Hongda Wu School of information engineering Communication University of China Beijing China

Text classification is the key technology for mining and organizing text information, which is the process of determining the text types automatically according to the content. Based on machine learning algorithm, text classification system includes four processes, namely text pretreatment, text representation, classifier training and classification. In this paper, a Chinese news text classification system model is designed. And in the classifier training part, we separately chose and compared K-nearest Neighbor, Naive Bayes, and Support Vector machine as our classification algorithm. Then, we tested and analyzed these classifiers with each other and finally got a conclusion. The experimental conclusion shows that the Chinese news text classification system can get satisfied results based on the machine learning algorithm.

关键词： Chinese text classification Chinese word segment Feature extraction machine learning algorithm

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Research on Gender Recognition of Names Based on machine learning algorithm

Research on Gender Recognition of Names Based on Machine Lea...

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International Conference on Intelligent Human-machine Systems and Cybernetics

作者： Qianjun Shuai Runze Wang Libiao Jin Long Pang School of information engineering Communication University of China Beijing China

The name has a rich connotation. In both English and Chinese, people's names usually have strong distinctions of gender. We can guess that strangers are male or female from their name. And the accuracy is high. This paper mainly makes the study of the gender recognition of Chinese names but it begins from the study of English gender recognition, step by step, looking for the rules, and use a variety of machine learning algorithms to search for a better model.

关键词： Gender recognition of names machine learning algorithm Classification Feature extraction

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Design and Application of machine learning algorithm Computer in Connect6 of Computer Games System 28

Design and Application of Machine Learning Algorithm Compute...

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28th Chinese Control and Decision Conference

作者： Wu, Gui Tao, Jun Jianghan Univ Educ Adm Off Wuhan 430056 Peoples R China Jianghan Univ Sch Math & Comp Sci Wuhan 430056 Peoples R China Rowan Univ Dept Elect & Comp Engn Glassboro NJ 08028 USA

ISBN: (纸本)9781467397148

The paper introduces briefly some of the key structures of the computer games system in connect6. And it mainly provides a further optimization for the current existing computer games system in connect6. The machine learning algorithm can increase the adaptive width adjustment in the MTD (f) algorithm and the self-learning method by TD_BP algorithm in the evaluation function which could strengthen the "thinking" ability on the computer games system in connect6. The advanced and modified algorithm is proved to be practical and applicative by experimentations and tests of computer games system in connect6 provided in this paper.

关键词： Connect6 machine learning algorithm Evaluation Function Computer Games

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A Novel Security algorithm RPBB31 for Securing the Social Media Analyzed Data using machine learning algorithms

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WIRELESS PERSONAL COMMUNICATIONS 2023年第1期131卷 581-608页

作者： Batcha, Bagath Basha Chan Singaravelu, Rajaprakash Ramachandran, Meenakumari Muthusamy, Suresh Panchal, Hitesh Thangaraj, Kokilavani Ravindaran, Ashokkumar Kommuri Pratap Reddy Inst Technol Dept Comp Sci & Engn Hyderabad Telangana India Vinayaka Missions Res Fdn Deemed Univ Aarupadai Veedu Inst Technol Dept Comp Sci & Engn Paiyanoor Tamil Nadu India Kongu Engn Coll Autonomous Dept Elect & Elect Engn Erode Tamil Nadu India Kongu Engn Coll Autonomous Dept Elect & Commun Engn Erode Tamil Nadu India Govt Engn Coll Dept Mech Engn Patan Gujarat India Sri Krishna Coll Engn & Technol Autonomous Dept Elect & Elect Engn Coimbatore Tamil Nadu India Bannari Amman Inst Technol Autonomous Dept Elect & Elect Engn Erode Tamil Nadu India

The present world data is most important in public because without data cannot live in the world. This data is big data and that data daily increases through Social Media like "Twitter, Facebook, Youtube, WhatsApp, Instagram, LinkedIn", etc.., because this media only share public opinion very fast through the net. From this media, more people used especially Twitter. Thus media are used to analyze the public opinion of the tweets and predict the future through machine learning algorithm. This analyzed data should make it polarity score. This score data has very little security because, this score can change the score and affected the future, so apply the existing security algorithms is Salsa and ChaCha. The Salsa algorithm is diagonal values moved to the first row. The ChaCha algorithm is diagonal values moved to the first column. The existing algorithms do not have good security because they focused only on performance, not security. So, the novel security algorithm is RPBB31. This algorithm has seven stages. The 1st stage is to find the secret key N, n, and p values from the matrix. The 2nd stage is to apply the secret key in P-N(n) operation. The 3rd stage operation of P-N(n) up to n = 1. The 4th stage is all P-N(n) operations make their single line. The 5th stage is to pair the values and swap the values in the matrix. The 6th stage is column operations in the matrix. The 7th stage is again Step 4 values used to swap but "0th" cell value start from reverse in the matrix. In world cricket is the most famous game. In all social media Millions of people are following in different manner, especially in indian cricketer are more famous in India and world. In some point of time it may lead to match fixing, betting. To overcome this kind of issue the four datasets chosen. The proposed algorithm has provide good security and performance while compare to existing algorithms.

关键词： Twitter machine learning algorithm Security Encryption RPBB31

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Wind speed forecast model for wind farm based on a hybrid machine learning algorithm

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INTERNATIONAL JOURNAL OF SUSTAINABLE ENERGY 2015年第1期34卷 38-51页

作者： Ul Haque, Ashraf Mandal, Paras Meng, Julian Negnevitsky, Michael Montana State Univ Dept Elect & Comp Engn Bozeman MT 59717 USA Univ Texas El Paso Dept Ind Mfg & Syst Engn El Paso TX 79968 USA Univ New Brunswick Dept Elect & Comp Engn Fredericton NB E3B 5A3 Canada Univ Tasmania Sch Engn Hobart Tas 7001 Australia

This paper presents a newstrategy for wind speed forecasting based on a hybrid machine learning algorithm, composed of a data filtering technique based onwavelet transform (WT) and a soft computing model based on the fuzzyARTMAP (FA) network. The prediction capability of the proposed hybrid WT + FA model is demonstrated by an extensive comparison with some other existing wind speed forecasting methods. The results show a significant improvement in forecasting error through the application of a proposed hybrid WT + FA model. The proposed wind speed forecasting strategy is applied to real data acquired from the North Cape wind farm located in PEI, Canada.

关键词： Fuzzy ARTMAP network machine learning algorithm short-term wind speed forecasting wavelet transform

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Design and Application of machine learning algorithm Computer in Connect6 of Computer Games System

Design and Application of Machine Learning Algorithm Compute...

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第28届中国控制与决策会议

作者： Gui Wu Jun Tao Educational Administration office Jianghan University School of Mathematics and Computer Science Jianghan University Department of Electrical & Computer Engineering Rowan University

ISBN: (纸本)9781467397155

The paper introduces briefly some of the key structures of the computer games system in *** it mainly provides a further optimization for the current existing computer games system in *** machine learning algorithm can increase the adaptive width adjustment in the MTD（f） algorithm and the self-learning method by TDP algorithm in the evaluation function which could strengthen the "thinking" ability on the computer games system in *** advanced and modified algorithm is proved to be practical and applicative by experimentations and tests of computer games system in connect6 provided in this paper.

关键词： Connect6 machine learning algorithm Evaluation Function Computer Games

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