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Breast Cancer Identification from Patients' Tweet Streaming Using Machine Learning Solution on Spark

Nahla F. Omran, Sara F. Abd-el Ghany, Hager Saleh, Ayman Nabil, Ahmed Mostafa Khalil
2021 Complexity  
This paper presented a real-time system to predict breast cancer based on streaming patient's health data from Twitter.  ...  The best model with the highest accuracy obtained from the first component predicts breast cancer in real time from tweets' streaming.  ...  on Apache Spark are used to train and test models to a Breast Cancer Wisconsin (Diagnostic) database (BCWD) to select the best model that is used to predict breast cancer in real time.  ... 
doi:10.1155/2021/6653508 fatcat:trbdi6cxnbgdniz3nuipvuf5oi

Feasibility Study on Data Mining Techniques in Diagnosis of Breast Cancer

Keerthana Rajendran, Asia Pacific University of Technology & Innovation, Kuala Lumpur 57000, Malaysia, Manoj Jayabalan, Vinesh Thiruchelvam, V. Sivakumar
2019 International Journal of Machine Learning and Computing  
This study reviews article provides a holistic view of the types of data mining techniques used in prediction of breast cancer.  ...  Index Terms-Breast cancer, data mining, early prediction.  ...  The priority based decision tree method on the SEER breast cancer dataset was employed to reduce the feature and improve computational time [24] .  ... 
doi:10.18178/ijmlc.2019.9.3.806 fatcat:emdwvc33jjbt3lyoblcjcspgoq

Automatic Classification on Bio Medical Prognosisof Invasive Breast Cancer

Sountharrajan S, Karthiga M, Suganya E, Rajan C
2017 Asian Pacific Journal of Cancer Prevention  
The proposed system beseech various data mining techniques together with a real-time input data from a biosensor device to determine the disease development proportion.  ...  The complete dataset are processed using data mining classification algorithms to predict the accuracy. The exactness of the proposed model is improved by ranking attributes by Ranker algorithm.  ...  Real-time output from a biosensor device improves the accuracy of disease prediction.  ... 
doi:10.22034/apjcp.2017.18.9.2541 pmid:28952297 pmcid:PMC5720663 fatcat:qdoqlrspfrfd3pef7cukzoz7q4

A Research on Breast Cancer Prediction using Data Mining Techniques

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Early detection and diagnosis of breast cancer plays a significant role in the welfare of women. The mortality rate due to breast cancer is on an all-time high.  ...  This research field affords most intelligent and reliable data mining models in breast cancer prediction and decision making.  ...  The advantage of using data mining in the disease diagnosis is that it can mine the large medical dataset within a short time. The prediction accuracy is high and reliable.  ... 
doi:10.35940/ijitee.k1058.09811s219 fatcat:r75bxhaepvhtlfqpwptdf34i3q

A Review on Data Mining Techniques for Prediction of Breast Cancer Recurrence

R.S.PadmaPriya, P. Senthil Vadivu
2019 Zenodo  
Data mining algorithms provide assistance in predicting the early-stage breast cancer that continually has been difficult analysis drawback.  ...  Large information like Clump, Classification, Association Rules, Prediction and Neural Networks, Decision Trees can be analyzed using data mining applications and techniques.  ...  were selected using statistical feature selection methods.  ... 
doi:10.5281/zenodo.3355235 fatcat:wozy2rjnsncfncyj3oylhsojey

A Novel Feature Selection Method for Effective Breast Cancer Diagnosis and Prognosis

T. Sridevi, A. Murugan
2014 International Journal of Computer Applications  
In the present study using the Breast cancer Wisconsin data sets, a feature selection algorithm Modified Correlation Rough Set Feature Selection (MCRSFS) predicts both diagnosis and prognosis by comparing  ...  A major area of current research in data mining is the field of medical diagnosis.  ...  To get high accuracy of a prediction model, optimal parameter setting play a crucial role.  ... 
doi:10.5120/15399-4026 fatcat:b75qaoeklrazje7hzepgeex6mi

SVM &Ga-clustering Based Feature Selection Approach for Breast Cancer Detection

Rashmi Priya, Syed Wajahat Abbas Rizvi
2020 International Journal on Soft Computing Artificial Intelligence and Applications  
Data mining is an important step of library discovery where intelligent methods are used to detect patterns.  ...  In recent decades, women's high prevalence of breast cancer has risen dramatically. This paper discussed several data analysis methods used to detect breast cancer early.  ...  It has joined a complex science area to address real-time theoretical problems. Big data mining is used in many areas where data analysis is needed.  ... 
doi:10.5121/ijscai.2020.9401 fatcat:bwsqedcd3rhgdjxtwpbe5kznom

Comparison of Different Techniques to Predict Disease in Agriculture Production - A Review

Manpreet Kaur, Department of Computer Applications, Guru Kashi University, Talwandi Sabo, PB, India
2020 International Journal of Engineering Research and  
Using predictive analysis techniques can help in solving this problem.  ...  Analyzing the data can help in improving the quality of decision making and help the clinician's to monitor the high risk area and provide specialized treatments.  ...  Use different type of data to check the behavior of proposed model and see behavior on multiclass classification problems Analysis and Prediction of Breast cancer and Diabetes Disease  ... 
doi:10.17577/ijertv9is080217 fatcat:qujmutkah5hgxpxumo7ay3pemm

A Survey on Data Mining Techniques for COVID Prediction

2021 International Journal of Emerging Trends in Engineering Research  
This also includes survey on data mining techniques, models and various datasets.  ...  A number of researchers are also working towards prediction of possibility of infection of COVID-19 among humans using machine learning techniques, specifically by applying data mining methods.  ...  Various types of diseases such as liver disorder, diabetes, breast cancer, thyroid illness, skin cancer, etc. can be predicted using data mining. R.  ... 
doi:10.30534/ijeter/2021/02982021 fatcat:dm642rrm5ba6foakeb3rop5zcy

Feature Selection Method using Genetic Algorithm for Medical Dataset

Neesha Jothi, Wahidah Husain, Nur'Aini Abdul Rashid, Sharifah Mashita Syed-Mohamad
2019 International Journal on Advanced Science, Engineering and Information Technology  
Therefore, a compelling feature selection method is important in this case to improve the correctly classify different diseases and consequently lead to help medical practitioners.  ...  This prediction method with GA as feature selection will help medical practitioners to make better diagnose with patient's disease.  ...  When the data mining model and the task are defined, the appropriate data mining method will be used to build the model based on the discipline of study.  ... 
doi:10.18517/ijaseit.9.6.10226 fatcat:e5f5xfe23zdcfmw3tu33t5jlqy

Hybrid Tolerance Rough Set

G. Jothi, H. Hannah Inbarani, Ahmad Taher Azar
2013 International Journal of Fuzzy System Applications  
This paper proposes an approach based on the tolerance rough set model, which has the flair to deal with real-valued data whilst simultaneously retaining dataset semantics.  ...  Feature Selection is a process of selecting most enlightening features from the data set which preserves the original significance of the features following reduction.  ...  Feature selection, as a preprocessing step to machine learning, is effective in reducing dimensionality, removing irrelevant data, increasing predictive accuracy, and improving result comprehensibility  ... 
doi:10.4018/ijfsa.2013100102 fatcat:tgd7n34ebfdmdgxxzwwksiqzoi

Data mining and medical world: breast cancers' diagnosis, treatment, prognosis and challenges

Rozita Jamili Oskouei, Nasroallah Moradi Kor, Saeid Abbasi Maleki
2017 American Journal of Cancer Research  
This investigation attempts to provide a comprehensive survey about applications of data mining techniques in breast cancer diagnosis, treatment & prognosis till now.  ...  The amount of data in electronic and real world is constantly on the rise. Therefore, extracting useful knowledge from the total available data is very important and time consuming task.  ...  , and inconsistent or no quality data. • Transformation: includes smoothing, aggregation, generalization or normalization and attribute/feature selection. • Data mining: applying data mining methods or  ... 
pmid:28401016 pmcid:PMC5385648 fatcat:2gw2k7kedzg7lowumlt6zaofga

SVM &GA-CLUSTERING BASED FEATURE SELECTION APPROACH FOR BREAST CANCER DETECTION

Dr. Rashmi Priya1 And Syed Wajahat2
2020 Zenodo  
Data mining is an important step of library discovery where intelligent methods are used to detect patterns.  ...  In recent decades, women's high prevalence of breast cancer has risen dramatically. This paper discussed several data analysis methods used to detect breast cancer early.  ...  It has joined a complex science area to address real-time theoretical problems. Big data mining is used in many areas where data analysis is needed.  ... 
doi:10.5281/zenodo.4304225 fatcat:smtadnxxtbfodnywfmdbcpfoli

Breast Cancer Diagnosis Via Data Mining: Performance Analysis of Seven Different Algorithms

Zehra Karapinar Senturk, Resul Kara
2014 Computer Science & Engineering An International Journal  
is tried to be predicted under cover of those data.  ...  In this study, it is intended to contribute to the early diagnosis of breast cancer. An analysis on breast cancer diagnoses for the patients is given.  ...  A hybrid SVM-based strategy with feature selection to render a diagnosis between the breast cancer and fibro adenoma and to find important risk factor for breast cancer is constructed.  ... 
doi:10.5121/cseij.2014.4104 fatcat:fywopnq6n5e3fo6lonwpjnrd4q

Improved Machine Learning-Based Predictive Models for Breast Cancer Diagnosis

Abdur Rasool, Chayut Bunterngchit, Luo Tiejian, Md. Ruhul Islam, Qiang Qu, Qingshan Jiang
2022 International Journal of Environmental Research and Public Health  
In this work, we proposed data exploratory techniques (DET) and developed four different predictive models to improve breast cancer diagnostic accuracy.  ...  The implementation procedure and findings can guide physicians to adopt an effective model for a practical understanding and prognosis of breast cancer tumors.  ...  The authors would also like to acknowledge Muhammad Saqlain Aslam for sharing the idea of this work.  ... 
doi:10.3390/ijerph19063211 pmid:35328897 pmcid:PMC8949437 fatcat:fcahw5o5kfbqlmjoxtzmhfigem
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