000			a
999			_c18252 _d18252
003			OSt
005			20221117113031.0
008			221117b xxu||||| |||| 00| 0 eng d
040			_aAIKTC-KRRC _cAIKTC-KRRC
100			_919103 _aNagalpara, Sirajali
245			_aDeep learning strategy for predicting liver cancer using convolutional neural network algorithm
250			_aVol.7(3), May-Jun
260			_aNew Delhi _bAssociated Management Consultants _c2022
300			_a43-49p.
520			_aOne 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%.
650		0	_94622 _aComputer Engineering
700			_919104 _aPatel, Bhavesh M.
773	0		_dNew Delhi Associated Management Consultants _tIndian Journal of Computer Science _x2456-4133
856			_uhttp://www.indianjournalofcomputerscience.com/index.php/tcsj/article/view/171270 _yClick here
942			_2ddc _cAR