Perbandingan Metode Jaringan Syaraf Tiruan Dalam Aplikasi Medis
DOI:
https://doi.org/10.35706/syji.v2i01.193Abstract
Abstrak - Dalam dunia medis aplikasi jaringan saraf tiruan banyak digunakan. Jaringan saraf tiruan mampu memprediksi dan menganalisis suatu masalah, dan sistem jaringan syaraf tiruan mampu menganalisis suatu masalah. Keterbatasan manusia dalam hal kemampuan untuk mendeteksi sesuatu dengan kuantitas objek yang tinggi sangat berpengaruh pada kondisi kemampuan daya tahan tubuh manusia, sehingga hasil akursi deteksi yang diharapkan jauh di bawah standar yang ditetapkan. Dengan menggunakan teknik kecerdasan buatan untuk melakukan deteksi objek yang mampu melakukan deteksi sesuai dengan akurasi standar yang ditetapkan. Pada penelitian ini tujuannya membandingkan beberapa metode kecerdasan buatan dalam aplikasi medis mengenai penyakit kanker. Hasil perbadingan dari berbagai metode kecerdasan buatan dalam aplikasi medis akan dapat dilihat metode yang banyak dipakai dan mampu memberikan tingkat nilai akurasi paling presisi.
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Kata Kunci:Â Jaringan saraf tiruan, Artificial Intelligence, Medis
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References
J. T. Batuello, E. J. Gamito, E. David C., Misop H., A. W. Partin, D. G. Mcleod, and C. O’Donnell. “Artificial Neural Network Model for The Asessment of Lymph Node Spread in Patients with Clinically Localized Prostate Cancerâ€. Elsevier Science Inc, Urology, Vol. 57, No. 3, 2001, pp 481-485.
P. Finne, R. Finne, A. Auvinen, H. Juusela, J. Aro, Liisa M. T. N., M. Hakama, S. Ranniko, Teuvo L. J. T., and U. H. Stenman. “Predicting The Outcome of Prostate Biopsy in Screen-Positive Men by A Multilayer Preception Networkâ€. Elsevier Science Inc, Urology, Vol. 56, No. 3, 2000, pp 418-422.
M. Cengiz C., Cemil C., Hasan K., Fieref S., and I. Barutcu. “Predicting Coronary Artery Disease Using Different Artificial Neural Network Modelsâ€. CAD and artificial neural network, 2008, pp 249-254.
A. Biglarian, E. Hajizadeh, A. Kazemnejad, and F. Zayeri. “Determining of Prognostic Factors in Gastric Cancer Patients Using Artificial Neural Networksâ€. Asian Pacific Journal of Cancer Prevention, Vol. 11, 2010, pp 533-536.
U. Ergun, Selami S., Farat H., and I. Guler. “Classification of Carotid Artery Stenosis of Patients with Diabetes by Neural Network and Logistic Regressionâ€. Elsevier Computers in Biology and Medicine, Vol. 34, 2004, pp 389-405.
M. R. Gohari, A. Biglarian, E. Bakhshi, and M. A. Pourhoseingholi. “Use of an Artificial Neural Network to Determine Prognostic Factors in Colorectal Cancer Patientsâ€. Asian Pacific Journal of Cancer Prevention, Vol. 12, 2011, pp 1469-1472.
Z. H. Zhou, Yuan J., Yu-Bin Y., and Shi-Fu C.. “Lung Cancer Cell Identification Based on Artificial Neural Network Ensemblesâ€. Elsevier Artificial Ingelligence in Medicine, Vol. 24, No. 1, 2002, pp 25-36.
Shirin A. Mojarad, Satnam S. Dlay, Wai L. Woo and Gajanan V. Sherbet. “Cross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural Networksâ€. Science Pub. American J. of Engineering and Applied Sciences, 2011, pp 576-585.
B. Larder, D. Wang, A. Revell, J. Montaner, R. Harrigan, F. De Wolf , J. Lange, S. Wegner, L. Ruiz, MarÃa J. P-E., S. Emery, J. Gatell , A. D‘Arminio M., C. Torti , M. Zazzi and C. Lane. “The Development of Artificial Neural Networks to Predict Virological Response to Combination HIV Therapyâ€. International Medical Press Antiviral Therapy, Vol. 12, 2007, pp 15-24.
J. Frounchi, G. Karimian, A. Keshtkar and Yu-Chu Tian. “An Artificial Neural Network Hardware for Bladder Cancerâ€. European Journal of Scientific Research, Vol. 27, No. 1, 2009, pp 46-45.
A. O. Osofisan, O. O. Adeyemo, B. A. Sawyerr, and O. Eweje. “Prediction of Kidney Failure Using Artificial Neural Networksâ€. European Journal of Scientific Research, Vol. 41, No. 4, 2011, pp 487-492.
D. R. Chowdhury, M. Chatterjee, and R. K. Samanta. “An Artificial Neural Network Model for Neonatal Disease Diagnosisâ€. International Journal of Artificial Intelligence and Expert Systems (IJAE), Vol. 2, Issue 3, 2011, pp 97-106.
D. Shanthi, G. Sahoo, and N. Saravanan. “Designing an Artificial Neural Network Model for the Prediction of Thrombo-embolic Strokeâ€. International Journals of Biometric and Bioinformatics (IJBB), Vol. 3, Issue 1, 2008, pp 10-18.
N. Ganesan, K. Venkatesh, M. A. Rama, and A. Malathi Palani. “Application of Neural Networks in Diagnosing Cancer Disease Using Demographic Dataâ€. International Journal of Computer Applications, Vol. 1, No. 26, 2010, pp 76-85.
I. Bonet, Maria M. GarcÃa, S. Salazar, R. Sanchez, Yvan Saeys, Yves Van de Peer, and R.Grau1. “Predicting Human Immunodeficiency Virus (HIV) Drug Resistance using Recurrent Neural Networksâ€. International Electronic Conference on Synthetic Organic Chemistry, 2006, pp 1-30.
Feng Xia, Wenhong Zhao, Youxian Sun and Yu-Chu Tian. “Recognition and prediction of leukemia with Artificial Neural Network (ANN)â€. Medical Journal of Islamic Republic of Iran, Vol. 25, No. 1, 2011, pp 35-39.
Organized by: Program Studi Informatika, Universitas Singaperbangsa Karawang
