Dr Moloud Abdar

Improved binary differential evolution with dimensionality reduction mechanism and binary stochastic search for feature selection

B Ahadzadeh, M Abdar, F Safara, L Aghaei, S Mirjalili, A Khosravi, S García, F Karray, U Acharya

(2024), Vol. 151, pp. 1-26, Applied Soft Computing, Amsterdam, The Netherlands, C1

SpinalNet: Deep Neural Network With Gradual Input

H Kabir, M Abdar, A Khosravi, S Jalali, A Atiya, S Nahavandi, D Srinivasan

(2023), Vol. 4, pp. 1165-1177, IEEE Transactions on Artificial Intelligence, Piscataway, NJ., C1

UncertaintyFuseNet: Robust uncertainty-aware hierarchical feature fusion model with Ensemble Monte Carlo Dropout for COVID-19 detection

M Abdar, S Salari, S Qahremani, H Lam, F Karray, S Hussain, A Khosravi, U Acharya, V Makarenkov, S Nahavandi

(2023), Vol. 90, pp. 364-381, Information Fusion, Netherlands, C1

SFE: A Simple, Fast and Efficient Feature Selection Algorithm for High-Dimensional Data

B Ahadzadeh, M Abdar, F Safara, A Khosravi, M Menhaj, P Suganthan

(2023), Vol. 27, pp. 1-16, IEEE Transactions on Evolutionary Computation, Piscataway, N.J., C1

Quantum face recognition protocol with ghost imaging

V Salari, D Paneru, E Saglamyurek, M Ghadimi, M Abdar, M Rezaee, M Aslani, S Barzanjeh, E Karimi

(2023), Vol. 13, pp. 2401-, Scientific reports, England, C1

Toxicity Prediction in Pelvic Radiotherapy Using Multiple Instance Learning and Cascaded Attention Layers

B Elhaminia, A Gilbert, J Lilley, M Abdar, A Frangi, A Scarsbrook, A Appelt, A Gooya

(2023), Vol. 27, pp. 1958-1966, IEEE Journal of Biomedical and Health Informatics, Piscataway, N.J., C1

Synthetic Datasets for Numeric Uncertainty Quantification: Proposing Datasets for Future Researchers

H Kabir, Moloud Abdar, Abbas Khosravi, Darius Nahavandi, Subrota Mondal, Sadia Khanam, Shady Mohamed, Dipti Srinivasan, Saeid Nahavandi, Ponnuthurai Suganthan

(2023), Vol. 9, pp. 39-48, IEEE Systems, Man, and Cybernetics Magazine, Piscataway, N.J., C1

Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review

Zeinab Sherkatghanad, Moloud Abdar, Jeremy Charlier, Vladimir Makarenkov

(2023), Vol. 24, pp. 1-25, Briefings in Bioinformatics, Oxford, Eng., C1

An Optimal Nonlinear Model Predictive Control-Based Motion Cueing Algorithm Using Cascade Optimization and Human Interaction

Mohammad Qazani, Houshyar Asadi, Yutao Chen, Moloud Abdar, Mansour Karkoub, Shady Mohamed, Chee Lim, Saeid Nahavandi

(2023), pp. 1-12, IEEE Transactions on Intelligent Transportation Systems, Piscataway, N.J., C1

Binarized multi-gate mixture of Bayesian experts for cardiac syndrome X diagnosis: A clinician-in-the-loop scenario with a belief-uncertainty fusion paradigm

M Abdar, A Mehrzadi, M Goudarzi, F Masoudkabir, L Rundo, M Mamouei, E Sala, A Khosravi, V Makarenkov, U Acharya, S Saadatagah, M Naderian, S García, N Sarrafzadegan, S Nahavandi

(2023), Vol. 97, pp. 1-20, Information Fusion, Amsterdam, The Netherlands, C1

Hybrid genetic-discretized algorithm to handle data uncertainty in diagnosing stenosis of coronary arteries

R Alizadehsani, M Roshanzamir, M Abdar, A Beykikhoshk, A Khosravi, S Nahavandi, P Plawiak, R Tan, U Acharya

(2022), Vol. 39, pp. 1-17, Expert Systems, London, Eng., C1

MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification

Z Senousy, M Abdelsamea, M Gaber, M Abdar, R Acharya, A Khosravi, S Nahavandi

(2022), pp. 1-12, IEEE Transactions on Biomedical Engineering, Piscataway, N.J., C1

Hercules: Deep Hierarchical Attentive Multi-Level Fusion Model with Uncertainty Quantification for Medical Image Classification

M Abdar, M Fahami, L Rundo, P Radeva, A Frangi, U Acharya, A Khosravi, H Lam, A Jung, S Nahavandi

(2022), pp. 1-13, IEEE Transactions on Industrial Informatics, Piscataway, N.J., C1

A Review of Generalized Zero-Shot Learning Methods

F Pourpanah, M Abdar, Y Luo, X Zhou, R Wang, C Lim, X Wang, Q Wu

(2022), pp. 1-20, IEEE Transactions on Pattern Analysis and Machine Intelligence, Piscataway, N.J., C1

Uncertainty-Aware Interpretable Deep Learning for Slum Mapping and Monitoring

T Fisher, H Gibson, Y Liu, M Abdar, M Posa, G Salimi-Khorshidi, A Hassaine, Y Cai, K Rahimi, M Mamouei

(2022), Vol. 14, Remote Sensing, C1

The need for quantification of uncertainty in artificial intelligence for clinical data analysis: increasing the level of trust in the decision-making process

Moloud Abdar, Abbas Khosravi, Sheikh Islam, U Acharya, Athanasios Vasilakos

(2022), Vol. 8, pp. 28-40, IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE, C1

Intelligent personalized shopping recommendation using clustering and supervised machine learning algorithms

N Chabane, A Bouaoune, R Tighilt, M Abdar, A Boc, E Lord, N Tahiri, B Mazoure, U Rajendra Acharya, V Makarenkov

(2022), Vol. 17, pp. e0278364-e0278364, PLoS ONE, United States, C1

Hybrid particle swarm optimization for rule discovery in the diagnosis of coronary artery disease

M Zomorodi-moghadam, M Abdar, Z Davarzani, X Zhou, P Pławiak, U Acharya

(2021), Vol. 38, Expert Systems, C1

ABCDM: an attention-based bidirectional CNN-RNN deep model for sentiment analysis

Mohammad Basiri, Shahla Nemati, Moloud Abdar, Erik Cambria, U Acharrya

(2021), Vol. 115, pp. 279-294, Future generation computer systems, Amsterdam, The Netherlands, C1

Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991-2020

R Alizadehsani, A Khosravi, M Roshanzamir, M Abdar, N Sarrafzadegan, D Shafie, F Khozeimeh, A Shoeibi, S Nahavandi, M Panahiazar, A Bishara, R Beygui, R Puri, S Kapadia, R Tan, U Acharya

(2021), Vol. 128, Computers in Biology and Medicine, United States, C1

Analysis of Driver Performance Using Hybrid of Weighted Ensemble Learning Technique and Evolutionary Algorithms

A Koohestani, M Abdar, S Hussain, A Khosravi, D Nahavandi, S Nahavandi, R Alizadehsani

(2021), Vol. 46, pp. 3567-3580, Arabian Journal for Science and Engineering, C1

Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991-2020)

R Alizadehsani, M Roshanzamir, S Hussain, A Khosravi, A Koohestani, M Zangooei, M Abdar, A Beykikhoshk, A Shoeibi, A Zare, M Panahiazar, S Nahavandi, D Srinivasan, A Atiya, U Acharya

(2021), Annals of Operations Research, United States, C1

Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning

M Abdar, M Samami, S Dehghani Mahmoodabad, T Doan, B Mazoure, R Hashemifesharaki, L Liu, A Khosravi, U Acharya, V Makarenkov, S Nahavandi

(2021), Vol. 135, Computers in Biology and Medicine, United States, C1

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

M Abdar, F Pourpanah, S Hussain, D Rezazadegan, L Liu, M Ghavamzadeh, P Fieguth, X Cao, A Khosravi, U Acharya, V Makarenkov, S Nahavandi

(2021), Vol. 76, pp. 243-297, Information Fusion, Amsterdam, The Netherlands, C1

A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets

M Basiri, S Nemati, M Abdar, S Asadi, U Acharrya

(2021), Vol. 228, pp. 1-21, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

Automated detection of shockable ECG signals: A review

M Hammad, R Kandala, A Abdelatey, M Abdar, M Zomorodi‐Moghadam, R Tan, U Acharya, J Pławiak, R Tadeusiewicz, V Makarenkov, N Sarrafzadegan, A Khosravi, S Nahavandi, A EL-Latif, P Pławiak

(2021), Vol. 571, pp. 580-604, Information Sciences, Amsterdam, The Netherlands, C1

BARF: A new direct and cross-based binary residual feature fusion with uncertainty-aware module for medical image classification

M Abdar, M Fahami, S Chakrabarti, A Khosravi, P Pławiak, U Acharya, R Tadeusiewicz, S Nahavandi

(2021), Vol. 577, pp. 353-378, Information Sciences, Amsterdam, The Netherlands, C1

A novel approach based on genetic algorithm to speed up the discovery of classification rules on GPUs

M Beheshti Roui, M Zomorodi, M Sarvelayati, M Abdar, H Noori, P Pławiak, R Tadeusiewicz, X Zhou, A Khosravi, S Nahavandi, U Acharya

(2021), Vol. 231, Knowledge-Based Systems, C1

Model uncertainty quantification for diagnosis of each main coronary artery stenosis

R Alizadehsani, M Roshanzamir, M Abdar, A Beykikhoshk, M Zangooei, A Khosravi, S Nahavandi, R Tan, U Acharya

(2020), Vol. 24, pp. 10149-10160, Soft Computing, Berlin, Germany, C1

Insights into relevant knowledge extraction techniques: a comprehensive review

A Shahid, M Afzal, M Abdar, M Basiri, X Zhou, N Yen, J Chang

(2020), Vol. 76, pp. 1695-1733, Journal of supercomputing, New York, N.Y., C1

DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring

P Pławiak, M Abdar, J Pławiak, V Makarenkov, U Acharya

(2020), Vol. 516, pp. 401-418, Information Sciences, Amsterdam, The Netherlands, C1

Improving Sentiment Polarity Detection through Target Identification

M Basiri, M Abdar, A Kabiri, S Nemati, X Zhou, F Allahbakhshi, N Yen

(2020), Vol. 7, pp. 113-128, IEEE Transactions on Computational Social Systems, Piscataway, N.J., C1

A new nested ensemble technique for automated diagnosis of breast cancer

M Abdar, M Zomorodi-Moghadam, X Zhou, R Gururajan, X Tao, P Barua, R Gururajan

(2020), Vol. 132, pp. 123-131, Pattern Recognition Letters, Amsterdam, The Netherlands, C1

The effect of aggregation methods on sentiment classification in Persian reviews

M Basiri, A Kabiri, M Abdar, W Mashwani, N Yen, J Hung

(2020), Vol. 14, pp. 1394-1421, Enterprise Information Systems, London, Eng., C1

Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network

Z Sherkatghanad, M Akhondzadeh, S Salari, M Zomorodi-Moghadam, M Abdar, U Acharya, R Khosrowabadi, V Salari

(2020), Vol. 13, pp. 1-12, Frontiers in Neuroscience, Lausanne, Switzerland, C1

A mixed solution-based high agreement filtering method for class noise detection in binary classification

M Samami, E Akbari, M Abdar, P Plawiak, H Nematzadeh, M Basiri, V Makarenkov

(2020), Vol. 553, pp. 1-28, Physica A: Statistical Mechanics and its Applications, Amsterdam, The Netherlands, C1

Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach

E Nasarian, M Abdar, M Fahami, R Alizadehsani, S Hussain, M Basiri, M Zomorodi-Moghadam, X Zhou, P Pławiak, U Acharya, R Tan, N Sarrafzadegan

(2020), Vol. 133, pp. 33-40, Pattern recognition letters, Amsterdam, The Netherlands, C1

Energy choices in Alaska: Mining people's perception and attitudes from geotagged tweets

M Abdar, M Basiri, J Yin, M Habibnezhad, G Chi, S Nemati, S Asadi

(2020), Vol. 124, pp. 1-15, Renewable and Sustainable Energy Reviews, Amsterdam, The Netherlands, C1

A comprehensive analysis of adverb types for mining user sentiments on amazon product reviews

U Chauhan, M Afzal, A Shahid, M Abdar, M Basiri, X Zhou

(2020), Vol. 23, pp. 1811-1829, World wide web, [New York, N.Y.], C1

Analysis of user preference and expectation on shared economy platform: An examination of correlation between points of interest on Airbnb

M Abdar, N Yen

(2020), Vol. 107, pp. 1-16, Computers in Human Behavior, Amsterdam, The Netherlands, C1

A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques

M Basiri, M Abdar, M Cifci, S Nemati, U Acharya

(2020), Vol. 198, pp. 1-19, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

Automated detection of presymptomatic conditions in spinocerebellar ataxia type 2 using monte carlo dropout and deep neural network techniques with electrooculogram signals

C Stoean, R Stoean, M Atencia, M Abdar, L Velázquez-Pérez, A Khosravi, S Nahavandi, U Rajendra Acharya, G Joya

(2020), Vol. 20, Sensors (Switzerland), Switzerland, C1-1

A novel facial image recognition method based on perceptual hash using quintet triple binary pattern

T Tuncer, S Dogan, M Abdar, P Pławiak

(2020), Vol. 79, pp. 29573-29593, Multimedia tools and applications, New York, N.Y., C1

Insights into relevant knowledge extraction techniques: a comprehensive review

Abdul Shahid, Muhammad Afzal, Moloud Abdar, Mohammad Basiri, Xujuan Zhou, Neil Yen, Jia-Wei Chang

(2020), Vol. 76, pp. 1695-1733, JOURNAL OF SUPERCOMPUTING, C1

IAPSO-AIRS: A novel improved machine learning-based system for wart disease treatment

M Abdar, V Wijayaningrum, S Hussain, R Alizadehsani, P Plawiak, U Acharya, V Makarenkov

(2019), Vol. 43, Journal of Medical Systems, United States, C1

Machine learning-based coronary artery disease diagnosis: A comprehensive review

R Alizadehsani, M Abdar, M Roshanzamir, A Khosravi, P Kebria, F Khozeimeh, S Nahavandi, N Sarrafzadegan, U Acharya

(2019), Vol. 111, Computers in Biology and Medicine, United States, C1

Integration of Ensemble and Evolutionary Machine Learning Algorithms for Monitoring Diver Behavior Using Physiological Signals

A Koohestani, M Abdar, A Khosravi, S Nahavandi, M Koohestani

(2019), Vol. 7, pp. 98971-98992, IEEE Access, C1

A database for using machine learning and data mining techniques for coronary artery disease diagnosis

R Alizadehsani, M Roshanzamir, M Abdar, A Beykikhoshk, A Khosravi, M Panahiazar, A Koohestani, F Khozeimeh, S Nahavandi, N Sarrafzadegan

(2019), Vol. 6, Scientific Data, England, C1

Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring

P Pławiak, M Abdar, U Rajendra Acharya

(2019), Vol. 84, pp. 1-14, Applied Soft Computing Journal, Amsterdam, The Netherlands, C1

A new machine learning technique for an accurate diagnosis of coronary artery disease

M Abdar, W Książek, U Acharya, R Tan, V Makarenkov, P Pławiak

(2019), Vol. 179, pp. 1-11, Computer Methods and Programs in Biomedicine, Shannon, Ireland, C1

A novel machine learning approach for early detection of hepatocellular carcinoma patients

W Książek, M Abdar, U Acharya, P Pławiak

(2019), Vol. 54, pp. 116-127, Cognitive Systems Research, Amsterdam, The Netherlands, C1

CWV-BANN-SVM ensemble learning classifier for an accurate diagnosis of breast cancer

M Abdar, V Makarenkov

(2019), Vol. 146, pp. 557-570, Measurement: Journal of the International Measurement Confederation, Amsterdam, The Netherlands, C1

Face recognition with triangular fuzzy set-based local cross patterns inwavelet domain

T Tuncer, S Dogan, M Abdar, M Basiri, P Pławiak

(2019), Vol. 11, pp. 1-18, Symmetry, Basel, Switzerland, C1

Decision Tree Predictive Learner-Based Approach for False Alarm Detection in ICU

T Manna, A Swetapadma, M Abdar

(2019), Vol. 43, pp. 1-13, Journal of Medical Systems, Berlin, Germany, C1

NE-nu-SVC: A New Nested Ensemble Clinical Decision Support System for Effective Diagnosis of Coronary Artery Disease

M Abdar, U Acharya, N Sarrafzadegan, V Makarenkov

(2019), Vol. 7, pp. 167605-167620, IEEE Access, Piscataway, N.J., C1

A Hybrid Latent Space Data Fusion Method for Multimodal Emotion Recognition

S Nemati, R Rohani, M Basiri, M Abdar, N Yen, V Makarenkov

(2019), Vol. 7, pp. 172948-172964, IEEE Access, Piscataway, N.J., C1

Improving the Diagnosis of Liver Disease Using Multilayer Perceptron Neural Network and Boosted Decision Trees

M Abdar, N Yen, J Hung

(2018), Vol. 38, pp. 953-965, Journal of Medical and Biological Engineering, Heidelberg, Germany, C1

Event-based trend factor analysis based on hashtag correlation and temporal information mining

H Lee, M Abdar, N Yen

(2018), Vol. 71, pp. 1204-1215, Applied Soft Computing, Amsterdam, The Netherlands, C1

Predicting risk of acute appendicitis: A comparison of artificial neural network and logistic regression models

L Shahmoradi, R Safdari, M Mirhosseini, G Arji, B Jannat, M Abdar

(2018), Vol. 56, pp. 784-795, Acta Medica Iranica, Tehran, Iran, C1

Understanding regional characteristics through crowd preference and confidence mining in P2P accommodation rental service

M Abdar, N Yen

(2017), Vol. 35, pp. 521-541, Library Hi Tech, Bingley, Eng., C1

Design of a universal user model for dynamic crowd preference sensing and decision-making behavior analysis

M Abdar, N Yen

(2017), Vol. 5, pp. 24842-24852, IEEE Access, Piscataway, N.J., C1

Performance analysis of classification algorithms on early detection of liver disease

M Abdar, M Zomorodi-Moghadam, R Das, I Ting

(2017), Vol. 67, pp. 239-251, Expert Systems with Applications, Amsterdam, The Netherlands, C1

Comparing performance of data mining algorithms in prediction heart diseases

M Abdar, M Abdar, S Kalhori, S Kalhori, T Sutikno, T Sutikno, I Subroto, I Subroto, G Arji, G Arji

(2015), Vol. 5, pp. 1569-1576, International journal of electrical and computer engineering, Yogyakarta, Indonesia, C1