Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques

Machine learning offers significant potential for lung cancer detection, enabling early diagnosis and potentially improving patient outcomes. Feature extraction remains a crucial challenge in this domain. Combining the most relevant features can further enhance detection accuracy. This study employe...

תיאור מלא

מידע ביבליוגרפי
Main Authors:	Liangyu Li, Jing Yang, Lip Yee Por, Mohammad Shahbaz Khan, Rim Hamdaoui, Lal Hussain, Zahoor Iqbal, Ionela Magdalena Rotaru, Dan Dobrotă, Moutaz Aldrdery, Abdulfattah Omar
פורמט:	Article
שפה:	English
יצא לאור:	Elsevier 2024-02-01
סדרה:	Heliyon
נושאים:	Classification Haralick texture features Lung cancer types Autoencoder and gray-level co-occurrence (GLCM)
גישה מקוונת:	http://www.sciencedirect.com/science/article/pii/S2405844024022230

אינטרנט

http://www.sciencedirect.com/science/article/pii/S2405844024022230

Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques

אינטרנט

פריטים דומים