Diagnosis of breast cancer using case-based reasoning / (Record no. 4635)

MARC details
000 -LEADER
fixed length control field 02245nam a2200265 a 4500
001 - CONTROL NUMBER
control field vtls000076626
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204604.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140120t2012 my a f m 000 0 eng d eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0001986(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905131554
Level of effort used to assign nonsubject heading access points yusri
-- 201401201200
-- Fida
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) QA76.9.S88 N87 2012 rs Bc.
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Nurramlah Abu Nasir
245 10 - TITLE STATEMENT
Title Diagnosis of breast cancer using case-based reasoning /
Statement of responsibility, etc. Nurramlah Abu Nasir
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2012
300 ## - PHYSICAL DESCRIPTION
Extent xv, 74 p. :
Other physical details ill. ;
Dimensions 30 cm.+
Accompanying material 1 CD-ROM
502 ## - DISSERTATION NOTE
Dissertation note Project paper (Bachelor of Computer Science (Software Engineering) -- Universiti Malaysia Pahang - 2012
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography: p.42-45
520 3# - SUMMARY, ETC.
Summary, etc. The objective for this thesis is to develop an intelligent decision support application for diagnosis of breast cancer using Case-Based Reasoning (CBR) algorithm for predict the class of cancer for patients. The number of expertises in the medical domain about the breast cancer is limited. Many patients have to wait too long to get their result from the check-up. The experience medical staffs are decreasing in number. When they retired, the new staffs will be replacing their places. So they have to learn many things related to their work. The application is very useful in the management of the problem and aids the inexperience physicians to check their diagnosis. It is to help the expert doctors or medical staffs in their breast cancer diagnosis. The methodology used in the application is Rapid Application Development (RAD) because it promotes the accuracy application development and delivery and reduced the cycle time. The application used the 100 data of Wisconsin Breast Cancer dataset for evaluating the CBR algorithm. This dataset is retrieved from UCI Machine Learning. The data used in this application consists of 9 attributes where the result of each case will be classified either non-cancerous (benign) or cancerous (malignant) group.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element System design
General subdivision Data processing
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Management information systems
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Software engineering
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost   Not for loan UMPLIB GAMBANG UMPLIB GAMBANG 04/09/2019   CD 6805 | QA76.9.S88 N87 2012 rs Bc. 0000071509 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   QA76.9.S88 N87 2012 rs Bc. 0000071508 04/09/2019 1 04/09/2019 Final Year Report

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