@inproceedings{f90bde068ba24cb2a9f3a41a0d0d919d,
title = "Automated classification of histological subtypes of NSCLC using support vector machines with radiomic features",
abstract = "Histological subtypes, i.e. adenocarcinoma (ADN) and squamous cell carcinoma (SCC), identified from a single biopsy occasionally differ from those from actual surgical resections in NSCLC. For increasing the classification accuracy, we aim to develop an automated approach for classifying histological subtypes of NSCLC using Gaussian, linear and polynomial support vector machines (SVMs) with radiomic features. Classification models of Gaussian, linear and polynomial SVMs constructed with radiomic features achieved the areas under the curves of 0.7542, 0.7522 and 0.7531, respectively. Histological subtypes of NSCLC could be classified into ADN and SCC using a Gaussian SVM with radiomic features.",
author = "Masahiro Yamada and Hidetaka Arimura and Kenta Ninomiya and Mazen Soufi",
year = "2019",
doi = "10.1117/12.2521511",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Kim, {Jong Hyo} and Hiroshi Fujita and Feng Lin",
booktitle = "International Forum on Medical Imaging in Asia 2019",
address = "United States",
note = "International Forum on Medical Imaging in Asia 2019 ; Conference date: 07-01-2019 Through 09-01-2019",
}