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Title: :  Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning
PaperId: :  19116
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 2 2023
DUI:    16.0415/IJARIIE-19116
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Dr. Amol PotgantwarSandip Institute of Technology and Research Centre (SITRC)
Kajal PatilSandip Institute of Technology and Research Centre (SITRC)
Sunidhi JainSandip Institute of Technology and Research Centre (SITRC)
Poonam JadhavSandip Institute of Technology and Research Centre (SITRC)
Komal BhadaneSandip Institute of Technology and Research Centre (SITRC)

Abstract

Computer Engineering
Mammography, deep learning, convolutional neural network, augmentation.
In today's world, cancer is a major public health concern. Breast cancer is a type of cancer that begins in the breast and spreads to the rest of the body. Breast cancer is one of the leading causes of death in women. Cancer occurs when cells become uncontrollably large. There are several types of breast cancer. The model proposed addressed both benign and malignant breast cancer. Breast cancer identification and classification using histopathology and ultrasound images are critical steps in computer-aided diagnosis systems. Researchers have demonstrated the ability to automate the initial level identification and classification of tumors over the last few decades. Breast cancer can be detected early, allowing patients to receive the appropriate treatment and improve their chances of survival. Deep learning (DL) and machine learning (ML) techniques are used to solve many medical problems. Several previous scientific studies on the categorization and identification of cancer tumors using various types of models have been published in the literature, but they have some limitations. The lack of a dataset, on the other hand, makes research difficult. Using the deep learning technique, the proposed methodology was created to aid in the automatic detection and diagnosis of breast cancer.

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IJARIIE Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. "Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 2 2023 Page 60-64
MLA Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. "Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning." International Journal Of Advance Research And Innovative Ideas In Education 9.2(2023) : 60-64.
APA Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, & Komal Bhadane. (2023). Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning. International Journal Of Advance Research And Innovative Ideas In Education, 9(2), 60-64.
Chicago Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. "Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 2 (2023) : 60-64.
Oxford Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. 'Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 2, 2023, p. 60-64. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Detection_of_Breast_Cancer_from_Histopathology_image_and_Classifying_Benign_and_Malignant_State_Using_Machine_learning_ijariie19116.pdf (Accessed : 26 May 2023).
Harvard Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. (2023) 'Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning', International Journal Of Advance Research And Innovative Ideas In Education, 9(2), pp. 60-64IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Detection_of_Breast_Cancer_from_Histopathology_image_and_Classifying_Benign_and_Malignant_State_Using_Machine_learning_ijariie19116.pdf (Accessed : 26 May 2023)
IEEE Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane, "Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 2, pp. 60-64, Mar-App 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Detection_of_Breast_Cancer_from_Histopathology_image_and_Classifying_Benign_and_Malignant_State_Using_Machine_learning_ijariie19116.pdf [Accessed : 26 May 2023].
Turabian Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. "Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 2 (26 May 2023).
Vancouver Dr. Amol Potgantwar, Kajal Patil, Sunidhi Jain, Poonam Jadhav, and Komal Bhadane. Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : 26 May 2023]; 9(2) : 60-64. Available from: https://ijariie.com/AdminUploadPdf/Detection_of_Breast_Cancer_from_Histopathology_image_and_Classifying_Benign_and_Malignant_State_Using_Machine_learning_ijariie19116.pdf
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