000 02245nam a2200265 a 4500
001 vtls000076626
003 KUKTEM
005 20251114204604.0
008 140120t2012 my a f m 000 0 eng d eng d
020 _aTHE0001986(Local)
039 9 _a201905131554
_byusri
_y201401201200
_zFida
040 _aUMP
090 _aQA76.9.S88 N87 2012 rs Bc.
100 0 _aNurramlah Abu Nasir
245 1 0 _aDiagnosis of breast cancer using case-based reasoning /
_cNurramlah Abu Nasir
260 _aKuantan, Pahang :
_bUMP,
_c2012
300 _axv, 74 p. :
_bill. ;
_c30 cm.+
_e1 CD-ROM
502 _aProject paper (Bachelor of Computer Science (Software Engineering) -- Universiti Malaysia Pahang - 2012
504 _aBibliography: p.42-45
520 3 _aThe 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 _aSystem design
_xData processing
650 0 _aManagement information systems
650 0 _aSoftware engineering
999 _aVIRTUA40
_c4635
_d4641
999 _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992