JHSM
Journal of Health Sciences and Medicine

Journal of Health Sciences and Medicine (JHSM) is an unbiased, peer-reviewed, and open access international medical journal. The Journal publishes interesting clinical and experimental research conducted in all fields of medicine, interesting case reports, and clinical images, invited reviews, editorials, letters, comments, and related knowledge.

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Original Article
Evaluation of artificial neural network and adaptive-network-based fuzzy inference system for ovarian and lung cancer prediction
Abstract
Aims: Every year, a significant number of individuals lose their lives due to cancer or undergo challenging treatments. Indeed, the development of an effective cancer prediction method holds great importance in the field of healthcare.
Methods: Machine learning methods have played a significant role in advancing cancer prediction models. In this context, this study focuses on exploring the potential of two machine learning methods: Artificial neural network (ANN) and adaptive-network-based fuzzy inference system (ANFIS) for cancer prediction. In this study, two different types of cancer, ovarian cancer and lung cancer, are taken into consideration. For the prediction of ovarian cancer, three specific biomarkers, namely human epididymis protein 4 (HE4), carbohydrate antigen 125 (CA-125), and carcinoembryonic antigen (CEA), are used to develop a prediction model. For the prediction of lung cancer, six different variables are utilized in the development of both the ANN and ANFIS methods.
Results: The findings demonstrated that the proposed methods had an accuracy rate of at least 93.9% in predicting ovarian cancer. With an accuracy rate of at least 89%, the proposed methods predicted lung cancer. Also, the proposed ANN method outperforms the ANFIS method in terms of predictive accuracy for both ovarian cancer and lung cancer.
Conclusion: This study suggests that the ANN method provides more reliable and accurate predictions for these specific cancer types based on the chosen variables or biomarkers. This study highlights the potential of machine learning methods, particularly ANN, in improving cancer prediction models and aiding in the early detection and effective management of ovarian and lung cancers.

Keywords : ANN, ANFIS, cancer prediction

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Article available in :
Volume 7, Issue 1, 2024
Page : 80-88
https://doi.org/10.32322/jhsm.1360782
Article Information
Received : 15 Eyl 2023
Accepted : 25 Ara 2023
Published : 15 Oca 2024
Corresponding Author :

Semih Latif İpek: Department of Food Engineering, Faculty of Engineering, Adana Alparslan Türkeş Science and Technology University, Adana, Turkiye

[email protected]
Citation : İpek SL, Göktürk D. Evaluation of artificial neural network and adaptive-network-based fuzzy inference system for ovarian and lung cancer prediction. J Health Sci Med. 2024;7(1):80-88.

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