Image Processing Projects _ Pancreatic cancer detection using neural network
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![](https://www.facebook.com/dialog/feed?app_id=1767574003460647&link=https://pantechelearning.myinstamojo.com/product/image-processing-projects-_-pancreatic-cance&picture=https://storeassets.im-cdn.com/temp/cuploads/ap-south-1%3Afe8af277-4cd5-47f4-b708-2cf09cc993b0/pantechelearning/products/1615980840587PAN-IPM-019--3-.JPG&name=Image Processing Projects _ Pancreatic cancer detection using neural network&caption=undefined&description=<p class="ql-align-justify"><span style="color: rgb(51, 51, 51);">Pancreatic cancer is associated with poor clinical outcomes primarily due to the advanced stage at the time of diagnosis. Endoscopic harmonic ultrasound imaging (HI) is being used to characterize pancreatic masses. In this proposed method we using the ultrasound images for processing. The objective of this study was to evaluate the feasibility of pancreatic tumor detection by high-intensity focused ultrasound image. For detecting Pancreatic cancer mostly machine learning techniques are used. In this paper we proposed propoblastic neural network method for diagnosed Pancreatic cancer. The aim of this work is to compare and explain how NN and logistic algorithm provide better solution when its work with ensemble machine learning algorithms for diagnosing Pancreatic cancer even the variables are reduced. In this paper we used the Pancreatic Cancer dataset. When compared to related work from the literature, it is shown that the PNN approach with logistic algorithm is achieved 93.50% accuracy from another machine learning algorithm.</span></p>&redirect_uri=http://www.facebook.com)
Image Processing Projects _ Pancreatic cancer detection using neural network
₹
5,200
₹
6,000
13% off
Exclusive of taxes
Share this
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Pancreatic cancer is associated with poor clinical outcomes primarily due to the advanced stage at the time of diagnosis. Endoscopic harmonic ultrasound imaging (HI) is being used to characterize pancreatic masses. In this proposed me
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