| 000 -LEADER |
|---|
| fixed length control field |
a |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20221117113031.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
221117b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
AIKTC-KRRC |
| Transcribing agency |
AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
19103 |
| Author |
Nagalpara, Sirajali |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Deep learning strategy for predicting liver cancer using convolutional neural network algorithm |
| 250 ## - EDITION STATEMENT |
|---|
| Volume, Issue number |
Vol.7(3), May-Jun |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
New Delhi |
| Name of publisher, distributor, etc. |
Associated Management Consultants |
| Year |
2022 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Pagination |
43-49p. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
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%. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
4622 |
| Topical term or geographic name entry element |
Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
19104 |
| Co-Author |
Patel, Bhavesh M. |
| 773 0# - HOST ITEM ENTRY |
|---|
| Place, publisher, and date of publication |
New Delhi Associated Management Consultants |
| Title |
Indian Journal of Computer Science |
| International Standard Serial Number |
2456-4133 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| URL |
http://www.indianjournalofcomputerscience.com/index.php/tcsj/article/view/171270 |
| Link text |
Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Articles Abstract Database |
