Medical data classification using similarity measure of fuzzy soft set based distance measure
Medical data classification plays a crucial role in many medical imaging applications by automating or facilitating the delineation of medical images. A considerable amount of literature has been published on medical images classification based on data mining techniques to develop intelligent medica...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
UTEM
2017
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4874/1/AJ%202017%20%28685%29.pdf http://eprints.uthm.edu.my/4874/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833417708031442944 |
|---|---|
| author | Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina |
| author_facet | Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina |
| author_sort | Lashari, Saima Anwar |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Medical data classification plays a crucial role in many medical imaging applications by automating or facilitating the delineation of medical images. A considerable amount of literature has been published on medical images classification based on data mining techniques to develop intelligent medical decision support systems to help the physicians. This paper assesses the performance of a new classification algorithm using similarity measure fuzzy soft set based distance based for numerical medical datasets. The proposed modelling comprises of five phases explicitly: data acquisition, data pre-processing, data partitioning, classification using FussCyier and performance evaluation. The proposed classifier FussCyier is evaluated on five performance matrices’: accuracy, precision, recall, F-Micro and computational time. Experimental results indicate that the proposed classifier performed comparatively better with existing fuzzy soft classifiers. |
| format | Article |
| id | my.uthm.eprints-4874 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2017 |
| publisher | UTEM |
| record_format | eprints |
| spelling | my.uthm.eprints-48742021-12-23T04:15:41Z http://eprints.uthm.edu.my/4874/ Medical data classification using similarity measure of fuzzy soft set based distance measure Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina RC71-78.7 Examination. Diagnosis Including radiography T Technology (General) Medical data classification plays a crucial role in many medical imaging applications by automating or facilitating the delineation of medical images. A considerable amount of literature has been published on medical images classification based on data mining techniques to develop intelligent medical decision support systems to help the physicians. This paper assesses the performance of a new classification algorithm using similarity measure fuzzy soft set based distance based for numerical medical datasets. The proposed modelling comprises of five phases explicitly: data acquisition, data pre-processing, data partitioning, classification using FussCyier and performance evaluation. The proposed classifier FussCyier is evaluated on five performance matrices’: accuracy, precision, recall, F-Micro and computational time. Experimental results indicate that the proposed classifier performed comparatively better with existing fuzzy soft classifiers. UTEM 2017 Article PeerReviewed text en http://eprints.uthm.edu.my/4874/1/AJ%202017%20%28685%29.pdf Lashari, Saima Anwar and Ibrahim, Rosziati and Senan, Norhalina (2017) Medical data classification using similarity measure of fuzzy soft set based distance measure. Journal of Telecommunication, Electronic and Computer Engineering, 9 (2-9). pp. 95-99. ISSN 2289-8131 |
| spellingShingle | RC71-78.7 Examination. Diagnosis Including radiography T Technology (General) Lashari, Saima Anwar Ibrahim, Rosziati Senan, Norhalina Medical data classification using similarity measure of fuzzy soft set based distance measure |
| title | Medical data classification using similarity measure of fuzzy soft set based distance measure |
| title_full | Medical data classification using similarity measure of fuzzy soft set based distance measure |
| title_fullStr | Medical data classification using similarity measure of fuzzy soft set based distance measure |
| title_full_unstemmed | Medical data classification using similarity measure of fuzzy soft set based distance measure |
| title_short | Medical data classification using similarity measure of fuzzy soft set based distance measure |
| title_sort | medical data classification using similarity measure of fuzzy soft set based distance measure |
| topic | RC71-78.7 Examination. Diagnosis Including radiography T Technology (General) |
| url | http://eprints.uthm.edu.my/4874/1/AJ%202017%20%28685%29.pdf http://eprints.uthm.edu.my/4874/ |
| url_provider | http://eprints.uthm.edu.my/ |