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Erschienen in:
Assessment of the Perception of Usage of Facebook as a Business Tool in SMEs Through the Technological Acceptance Model (TAM) and Structural Equation Modeling Kapitel lesen Erstes Kapitel lesen

2023 | OriginalPaper | Buchkapitel

Breast Cancer Prediction Using Machine Learning and Image Processing Optimization

verfasst von : Nidal A. Al-Dmour, Raed A. Said, Haitham M. Alzoubi, Muhammad Alshurideh, Liaqat Ali

Erschienen in: The Effect of Information Technology on Business and Marketing Intelligence Systems

Verlag: Springer International Publishing

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Abstract

In this study, it is wanted to implement Naïve Bayes data mining techniques on a dataset gained from digitized Image of fine needle aspirate (or FNA) belonged to benign and malignant type of breast tumors. One of the most important factors causing cancers in the females, which can be measured from sample after maintaining in several hours’ laboratory sample preparation at certain condition. As an alternative, Image processing can be substituted by measuring the geometrical features of FNA are well adopted economically and efficiently.

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Vorheriges Kapitel Analysis of Issues Affecting IoT, AI, and Blockchain Convergence
Nächstes Kapitel Development of Data Mining Framework Cardiovascular Disease Prediction
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Metadaten
Titel
Breast Cancer Prediction Using Machine Learning and Image Processing Optimization
verfasst von
Nidal A. Al-Dmour
Raed A. Said
Haitham M. Alzoubi
Muhammad Alshurideh
Liaqat Ali
Copyright-Jahr
2023
Buch
The Effect of Information Technology on Business and Marketing Intelligence Systems

Print ISBN: 978-3-031-12381-8

Electronic ISBN: 978-3-031-12382-5

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-3-031-12382-5_113

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