@inproceedings{ce3ffeb5b94c4bfb931c209b0a42cf10,
title = "Malignancy prediction by using characteristic-based fuzzy sets: A preliminary study",
abstract = "Fuzzy sets approaches are widely used in medical diagnosis systems, since medical data is defined as uncertain, complex and subjective in most applications. In this paper we adapt and propose a fuzzy set based classification scheme for predicting malignancy of small pulmonary nodules. Our method basically consists of two steps: classification of nodule characteristics from image features and fuzzy set based inference engine for predicting malignancy. Results are compared with single classifiers which are trained on image features and with our previous methods. The results are promising for further development. Simple structure of the method makes it easier to implement and offers advantages over complex methods.",
keywords = "fuzzy sets, lung nodule, malignancy, nodule characteristic",
author = "Aydin Kaya and Can, \{Ahmet Burak\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2015 ; Conference date: 02-08-2015 Through 05-08-2015",
year = "2015",
month = nov,
day = "25",
doi = "10.1109/FUZZ-IEEE.2015.7338041",
language = "English",
series = "IEEE International Conference on Fuzzy Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Adnan Yazici and Pal, \{Nikhil R.\} and Uzay Kaymak and Trevor Martin and Hisao Ishibuchi and Chin-Teng Lin and Sousa, \{Joao M. C.\} and Bulent Tutmez",
booktitle = "FUZZ-IEEE 2015 - IEEE International Conference on Fuzzy Systems",
address = "United States",
}