Deep learning strategy for predicting liver cancer using convolutional neural network algorithm
By: Nagalpara, Sirajali
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Contributor(s): Patel, Bhavesh M.
Publisher: New Delhi Associated Management Consultants 2022Edition: Vol.7(3), May-Jun.Description: 43-49p.Subject(s): Computer EngineeringOnline resources: Click here
In:
Indian Journal of Computer ScienceSummary: One of the common types of cancer is liver cancer, early detection and diagnosis of which are critical. Discovery, decision, and aggressive therapy can prevent most cancer deaths. We use data mining approaches (Convolutional Neural Networks) to build prediction models for liver cancer with the most widely used statistical analysis methodology. Around 579 records and 10 variables were included in the data collection. The model was built, evaluated, and compared using a k-fold cross-validation process. CNN was the best accurate predictor for this domain with a test set accuracy of 100%.
| Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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Articles Abstract Database
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School of Engineering & Technology Archieval Section | Not for loan | 2022-2140 |
One of the common types of cancer is liver cancer, early detection and diagnosis of which are critical. Discovery, decision, and aggressive therapy can prevent most cancer deaths. We use data mining approaches (Convolutional Neural Networks) to build prediction models for liver cancer with the most widely used statistical analysis methodology. Around 579 records and 10 variables were included in the data collection. The model was built, evaluated, and compared using a k-fold cross-validation process. CNN was the best accurate predictor for this domain with a test set accuracy of 100%.
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