|
2020 Journal Article DGHNL: a new deep genetic hierarchical network of learners for prediction of credit scoringPławiak, Paweł, Abdar, Moloud, Pławiak, Joanna, Makarenkov, Vladimir and Acharya, U Rajendra (2020). DGHNL: a new deep genetic hierarchical network of learners for prediction of credit scoring. Information Sciences, 516, 401-418. doi: 10.1016/j.ins.2019.12.045 |
|
2020 Journal Article A new nested ensemble technique for automated diagnosis of breast cancerAbdar, Moloud, Zomorodi-Moghadam, Mariam, Zhou, Xujuan, Gururajan, Raj, Tao, Xiaohui, Barua, Prabal D. and Gururajan, Rashmi (2020). A new nested ensemble technique for automated diagnosis of breast cancer. Pattern Recognition Letters, 132, 123-131. doi: 10.1016/j.patrec.2018.11.004 |
|
2020 Journal Article Insights into relevant knowledge extraction techniques: a comprehensive reviewShahid, Abdul, Afzal, Muhammad Tanvir, Abdar, Moloud, Basiri, Mohammad Ehsan, Zhou, Xujuan, Yen, Neil Y. and Chang, Jia-Wei (2020). Insights into relevant knowledge extraction techniques: a comprehensive review. Journal of Supercomputing, 76 (3), 1695-1733. doi: 10.1007/s11227-019-03009-y |
|
2020 Journal Article A comprehensive analysis of adverb types for mining user sentiments on amazon product reviewsChauhan, Ummara Ahmed, Afzal, Muhammad Tanvir, Shahid, Abdul, Abdar, Moloud, Basiri, Mohammad Ehsan and Zhou, Xujuan (2020). A comprehensive analysis of adverb types for mining user sentiments on amazon product reviews. World Wide Web, 23 (3), 1811-1829. doi: 10.1007/s11280-020-00785-z |
|
2020 Journal Article Improving sentiment polarity detection through target identificationBasiri, Mohammad Ehsan, Abdar, Moloud, Kabiri, Arman, Nemati, Shahla, Zhou, Xujuan, Allahbakhshi, Forough and Yen, Neil Y. (2020). Improving sentiment polarity detection through target identification. IEEE Transactions on Computational Social Systems, 7 (1) 8911218, 113-128. doi: 10.1109/TCSS.2019.2951326 |
|
2020 Journal Article Automated detection of autism spectrum disorder using a convolutional neural networkSherkatghanad, Zeinab, Akhondzadeh, Mohammadsadegh, Salari, Soorena, Zomorodi-Moghadam, Mariam, Abdar, Moloud, Acharya, U. Rajendra, Khosrowabadi, Reza and Salari, Vahid (2020). Automated detection of autism spectrum disorder using a convolutional neural network. Frontiers in Neuroscience, 13 1325, 1-12. doi: 10.3389/fnins.2019.01325 |
|
2020 Journal Article The effect of aggregation methods on sentiment classification in Persian reviewsBasiri, Mohammad Ehsan, Kabiri, Arman, Abdar, Moloud, Mashwani, Wali Khan, Yen, Neil Y. and Hung, Jason C. (2020). The effect of aggregation methods on sentiment classification in Persian reviews. Enterprise Information Systems, 14 (9-10), 1394-1421. doi: 10.1080/17517575.2019.1669829 |
|
2019 Journal Article A hybrid latent space data fusion method for multimodal emotion recognitionNemati, Shahla, Rohani, Reza, Basiri, Mohammad Ehsan, Abdar, Moloud, Yen, Neil Y. and Makarenkov, Vladimir (2019). A hybrid latent space data fusion method for multimodal emotion recognition. IEEE Access, 7 8911364, 172948-172964. doi: 10.1109/access.2019.2955637 |
|
2019 Journal Article Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoringPławiak, Paweł, Abdar, Moloud and Rajendra Acharya, U. (2019). Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring. Applied Soft Computing Journal, 84 105740, 1-14. doi: 10.1016/j.asoc.2019.105740 |
|
2019 Journal Article CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancerAbdar, Moloud and Makarenkov, Vladimir (2019). CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer. Measurement: Journal of the International Measurement Confederation, 146, 557-570. doi: 10.1016/j.measurement.2019.05.022 |
|
2019 Journal Article A database for using machine learning and data mining techniques for coronary artery disease diagnosisAlizadehsani, R., Roshanzamir, M., Abdar, M., Beykikhoshk, A., Khosravi, A., Panahiazar, M., Koohestani, A., Khozeimeh, F., Nahavandi, S. and Sarrafzadegan, N. (2019). A database for using machine learning and data mining techniques for coronary artery disease diagnosis. Scientific Data, 6 227, 1-13. doi: 10.1038/s41597-019-0206-3 |
|
2019 Journal Article A new machine learning technique for an accurate diagnosis of coronary artery diseaseAbdar, Moloud, Książek, Wojciech, Acharya, U Rajendra, Tan, Ru-San, Makarenkov, Vladimir and Pławiak, Paweł (2019). A new machine learning technique for an accurate diagnosis of coronary artery disease. Computer Methods and Programs in Biomedicine, 179 104992, 1-11. doi: 10.1016/j.cmpb.2019.104992 |
|
2019 Journal Article Machine learning-based coronary artery disease diagnosis: A comprehensive reviewAlizadehsani, Roohallah, Abdar, Moloud, Roshanzamir, Mohamad, Khosravi, A., Kebria, Parham M., Khozeimeh, Fahime, Nahavandi, S., Sarrafzadegan, N. and Acharya, U. Rajendra (2019). Machine learning-based coronary artery disease diagnosis: A comprehensive review. Computers in Biology and Medicine, 111 103346, 1-14. doi: 10.1016/j.compbiomed.2019.103346 |
|
2019 Journal Article Corrigendum to “Performance Analysis of Classification Algorithms on early detection of Liver disease” (Expert Systems with Applications (2017) 67 (239–251), (S095741741630464X) (10.1016/j.eswa.2016.08.065))Abdar, Moloud, Zomorodi-Moghadam, Mariam, Das, Resul and Ting, I-Hsien (2019). Corrigendum to “Performance Analysis of Classification Algorithms on early detection of Liver disease” (Expert Systems with Applications (2017) 67 (239–251), (S095741741630464X) (10.1016/j.eswa.2016.08.065)). Expert Systems with Applications, 125, 442-443. doi: 10.1016/j.eswa.2019.02.029 |
|
2019 Journal Article IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatmentAbdar, Moloud, Wijayaningrum, Vivi Nur, Hussain, Sadiq, Alizadehsani, Roohallah, Plawiak, Pawel, Acharya, U. Rajendra and Makarenkov, Vladimir (2019). IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment. Journal of Medical Systems, 43 (7) 220, 1-23. doi: 10.1007/s10916-019-1343-0 |
|
2019 Journal Article Decision tree predictive learner-based approach for false alarm detection in ICUManna, Tishya, Swetapadma, Aleena and Abdar, Moloud (2019). Decision tree predictive learner-based approach for false alarm detection in ICU. Journal of Medical Systems, 43 (7) 191, 1-13. doi: 10.1007/s10916-019-1337-y |
|
2019 Journal Article Face recognition with triangular fuzzy set-based local cross patterns inwavelet domainTuncer, Turker, Dogan, Sengul, Abdar, Moloud, Basiri, Mohammad Ehsan and Pławiak, Paweł (2019). Face recognition with triangular fuzzy set-based local cross patterns inwavelet domain. Symmetry, 11 (6) 787, 1-18. doi: 10.3390/sym11060787 |
|
2019 Journal Article A novel machine learning approach for early detection of hepatocellular carcinoma patientsKsiążek, Wojciech, Abdar, Moloud, Acharya, U. Rajendra and Pławiak, Paweł (2019). A novel machine learning approach for early detection of hepatocellular carcinoma patients. Cognitive Systems Research, 54, 116-127. doi: 10.1016/j.cogsys.2018.12.001 |
|
2019 Conference Publication Performance improvement of decision trees for diagnosis of coronary artery disease using multi filtering approachAbdar, Moloud, Nasarian, Elham, Zhou, Xujuan, Bargshady, Ghazal, Wijayaningrum, Vivi Nur and Hussain, Sadiq (2019). Performance improvement of decision trees for diagnosis of coronary artery disease using multi filtering approach. 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS), Singapore, Singapore, 23-25 February 2019. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/CCOMS.2019.8821633 |
|
2019 Journal Article NE-nu-SVC: a new nested ensemble clinical decision support system for effective diagnosis of coronary artery diseaseAbdar, Moloud, Acharya, U. Rajendra, Sarrafzadegan, Nizal and Makarenkov, Vladimir (2019). NE-nu-SVC: a new nested ensemble clinical decision support system for effective diagnosis of coronary artery disease. IEEE Access, 7 8903185, 167605-167620. doi: 10.1109/access.2019.2953920 |
