Call for Papers:Vol.8 Issue.1

Submission
Last date		 27-Feb-2022
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-8,Issue-1. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Using Deep Ensemble Learning & Deep CNN For Cancer Prediction
PaperId: :  10569
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 5 Issue 3 2019
DUI:    16.0415/IJARIIE-10569
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Shreyas KulkarniManipal Institute of Technology

Abstract

Artificial Intelligence & Deep Learning
Carcinoma, Neural Network , Data Augmentation, Ensemble, Deep CNN.
Cancer is one of the dangerous diseases known to mankind. There are thousands of women who are affected by Cervical Cancer. Here we focus on classification of Lungs & cervical cancer cells .We aim here to minimize analytical errors while diagnosing the cancer .The project has many different types of cell classes .This cell are classified into cancer categories. The classification of Pap smear images to detect cervical dysplasia. This classification is to be done with deep learning methods. The main purpose here is to get better result and accuracy while detecting cervical dysplasia. Deep Neural Network with Convolutional Neural Network is used to classify the cells into different categories. Models are trained and tested with different parameters for better accuracy. Then they are ensembled with averaging of models. The models were able to produce pretty good results. The accuracy of predicted and true labels were high. This makes sense that using this methods to reduce the human errors will be significantly high and efficient. The models were able to produce accuracy above 80%, with ensemble it was higher than single models. This tells that if single models are ensembled with other different models then they can perform pretty good and then they can have much more higher accuracy than the single models. The project executed on CPU+GPU gives higher result than execution on CPU. The RAM of machine also plays important role in Time Complexity of model. GPU increase the performance of model and same time reduces the execution time. For this project Kaggle Online Cloud Library is used. Early detection of the cancer is an enormous challenge. Analysis and cure of lung malignancy have been one of the greatest difficulties faced by humans over the most recent couple of decades. For Lung Cancer, early identification of tumor would facilitate in sparing a huge number of lives over the globe consistently. This paper presents an approach which utilizes a Convolutional Neural Network (CNN) to classify the tumors found in lung as malignant or benign. The accuracy obtained by means of CNN is 96%, which is more efficient when compared to accuracy obtained by the traditional neural network systems.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Shreyas Kulkarni. "Using Deep Ensemble Learning & Deep CNN For Cancer Prediction" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 3 2019 Page 2066-2075
MLA Shreyas Kulkarni. "Using Deep Ensemble Learning & Deep CNN For Cancer Prediction." International Journal Of Advance Research And Innovative Ideas In Education 5.3(2019) : 2066-2075.
APA Shreyas Kulkarni. (2019). Using Deep Ensemble Learning & Deep CNN For Cancer Prediction. International Journal Of Advance Research And Innovative Ideas In Education, 5(3), 2066-2075.
Chicago Shreyas Kulkarni. "Using Deep Ensemble Learning & Deep CNN For Cancer Prediction." International Journal Of Advance Research And Innovative Ideas In Education 5, no. 3 (2019) : 2066-2075.
Oxford Shreyas Kulkarni. 'Using Deep Ensemble Learning & Deep CNN For Cancer Prediction', International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 3, 2019, p. 2066-2075. Available from IJARIIE, http://ijariie.com/AdminUploadPdf/Using_Deep_Ensemble_Learning___Deep_CNN_For_Cancer_Prediction_ijariie10569.pdf (Accessed : ).
Harvard Shreyas Kulkarni. (2019) 'Using Deep Ensemble Learning & Deep CNN For Cancer Prediction', International Journal Of Advance Research And Innovative Ideas In Education, 5(3), pp. 2066-2075IJARIIE [Online]. Available at: http://ijariie.com/AdminUploadPdf/Using_Deep_Ensemble_Learning___Deep_CNN_For_Cancer_Prediction_ijariie10569.pdf (Accessed : )
IEEE Shreyas Kulkarni, "Using Deep Ensemble Learning & Deep CNN For Cancer Prediction," International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 3, pp. 2066-2075, May-Jun 2019. [Online]. Available: http://ijariie.com/AdminUploadPdf/Using_Deep_Ensemble_Learning___Deep_CNN_For_Cancer_Prediction_ijariie10569.pdf [Accessed : ].
Turabian Shreyas Kulkarni. "Using Deep Ensemble Learning & Deep CNN For Cancer Prediction." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 5 number 3 ().
Vancouver Shreyas Kulkarni. Using Deep Ensemble Learning & Deep CNN For Cancer Prediction. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2019 [Cited : ]; 5(3) : 2066-2075. Available from: http://ijariie.com/AdminUploadPdf/Using_Deep_Ensemble_Learning___Deep_CNN_For_Cancer_Prediction_ijariie10569.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
ENHANCED IoE SECURITY BY GEO-TAGGED AGENT BASED SDNComputer Science & EngineeringKumar D Download
A Study of Different Knowledge Patterns in Diabetic Using Data Mining TechniquesCOMPUTER SCIENCE ENGINEERINGMalpe Kalpana Devidas Download
An efficient home automation system using IOT: A case study to benefit people with motion disability.IoTParas Garg Download
APPLICATIONS OF OPTIMIZATION FOR THE FOOD INDUSTRYComputer science and engineeringNguyen Thi Xuan Mai Download
Optimizing machine learning algorithms applied to the context of intelligent vehiclesComputer Science & EngineeringRAMAROLAHIVONJITIANA Frédéric Joël Download
“Design & Development of Healthcare Patient Monitoring System using Cloud Computing Environment"Computer Science and EngineeringMrs. Sonal Bawankule Download
ANALYSIS OF MACHINE LEARNING BASED COVID RISK ESTIMATIONComputer Science EngineeringAkansha Chokse Download
A REVIEW OF COVID RISK ESTIMATIONComputer Science EngineeringAkansha Chokse Download
A Comprehensive Review of Heart Disease Prediction Using Machine Learning ApproachMachine LearningShubha Soni Download
A New Secured Routing Protocol To Minimize the Risk of Link Failure in MANETcomputer EngineeringKOMAL PANDEY Download
A Study of Geometric Pattern Formation by Multiple Mobile RobotsComputer ScienceYadlapaty Srinivas Download
Enhancing the Data and Storage Security for Integrated Cloud and IoT System Using Secure Hash AlgorithmMachine LearningAyesha Siddiqha Mukthar Download
A STUDY OF DATA MINING TECHNIQUES FOR AUTOMATION ONTOLOGYComputer ScienceSreedhar Pulipati Download
SEMI-SUPERVISED MACHINE LEARNING APPROACH FOR DDOS DETECTIONcomputer engineering,AIMondi Surya Prabha, Download
Prediction of Student Performance Using Machine Learning TechniquesComputer Science and EngineeringMahesh Panjwani Download
12