Comparative Analysis of the Results of Algorithms for Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy Using Deep Learning

Fully Automated Echocardiogram Interpretation in Clinical Practice: Feasibility and Diagnostic Accuracy

Zhang, J., Gajjala, S., Agrawal, P., Tison, G. H., Hallock, L. A., Beussink-Nelson, L., Lassen, M. H., Fan, E., Aras, M. A., Jordan, C., et al. (2018) · Circulation · doi:10.1161/circulationaha.118.034338 · Cited by 1,006 · see citing works

Deep Learning in Medical Ultrasound Analysis: A Review

Liu, S., Wang, Y., Yang, X., Lei, B., Liu, L., Li, S. X., Ni, D., & Wang, T. (2019) · Engineering · doi:10.1016/j.eng.2018.11.020 · Cited by 798 · see citing works

Fast and accurate view classification of echocardiograms using deep learning

Madani, A., Arnaout, R., Mofrad, M., & Arnaout, R. (2018) · npj Digital Medicine · doi:10.1038/s41746-017-0013-1 · Cited by 585 · see citing works

Deep learning interpretation of echocardiograms

Ghorbani, A., Ouyang, D., Abid, A., He, B., Chen, J. H., Harrington, R. A., Liang, D. H., Ashley, E. A., & Zou, J. Y. (2020) · npj Digital Medicine · doi:10.1038/s41746-019-0216-8 · Cited by 518 · see citing works

Deep echocardiography: data-efficient supervised and semi-supervised deep learning towards automated diagnosis of cardiac disease

Madani, A., Ong, J. R., Tibrewal, A., & Mofrad, M. R. K. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0065-x · Cited by 250 · see citing works

Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography

Liu, F., Wang, K., Liu, D., Yang, X., & Tian, J. (2020) · Medical Image Analysis · doi:10.1016/j.media.2020.101873 · Cited by 119 · see citing works

A machine learning algorithm supports ultrasound-naïve novices in the acquisition of diagnostic echocardiography loops and provides accurate estimation of LVEF

Schneider, M., Bartko, P., Geller, W., Dannenberg, V., König, A., Binder, C., Goliasch, G., Hengstenberg, C., & Binder, T. (2021) · The International Journal of Cardiovascular Imaging · doi:10.1007/s10554-020-02046-6 · Cited by 98 · see citing works

Diagnosis and assessment of dilated cardiomyopathy: a guideline protocol from the British Society of Echocardiography

Mathew, T., Williams, L. K., Navaratnam, G., Rana, B. S., Wheeler, R., Collins, K., Harkness, A., Jones, R. E., Knight, D. S., O’Gallagher, K., et al. (2017) · Echo Research and Practice · doi:10.1530/erp-16-0037 · Cited by 95 · see citing works

Artificial Intelligence (AI)-Empowered Echocardiography Interpretation: A State-of-the-Art Review

Akkus, Z., Aly, Y. H., Attia, I. Z., López-Jiménez, F. A., Arruda-Olson, A. M., Pellikka, P. A., Pislaru, S. V., Kane, G. C., Friedman, P. A., & Oh, J. K. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10071391 · Cited by 90 · see citing works

Steps to use artificial intelligence in echocardiography

Kusunose, K. (2020) · Journal of Echocardiography · doi:10.1007/s12574-020-00496-4 · Cited by 66 · see citing works

Automatic Classification of Cardiac Views in Echocardiogram Using Histogram and Statistical Features

Balaji, N., Subashini, T. S., & Chidambaram, N. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.02.084 · Cited by 49 · see citing works

Detection and diagnosis of dilated cardiomyopathy and hypertrophic cardiomyopathy using image processing techniques

Balaji, N., Subashini, T. S., & Chidambaram, N. (2016) · Engineering Science and Technology an International Journal · doi:10.1016/j.jestch.2016.10.001 · Cited by 29 · see citing works

Interactive Translation in Echocardiography Training System With Enhanced Cycle-GAN

Teng, L., Fu, Z., & Yao, Y. (2020) · IEEE Access · doi:10.1109/access.2020.3000666 · Cited by 29 · see citing works

A Semi-Supervised Joint Learning Approach to Left Ventricular Segmentation and Motion Tracking in Echocardiography

Ta, K., Ahn, S. S., Lu, A., Stendahl, J. C., Sinusas, A. J., & Duncan, J. S. (2020) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi45749.2020.9098664 · Cited by 28 · see citing works

Accelerated Training for Convolutional Neural Networks

Musaev, M., & Rakhimov, M. (2020) · International Conference on Information Science and Communications Technologies (ICISCT) · doi:10.1109/icisct50599.2020.9351371 · Cited by 18 · see citing works

A New Approach to Classifying Myocardial Infarction and Cardiomyopathy Using Deep Learning

Nasimov, R., Muminov, B. B., Mirzakhalilov, S., & Nasimova, N. (2020) · International Conference on Information Science and Communications Technologies (ICISCT) · doi:10.1109/icisct50599.2020.9351386 · Cited by 17 · see citing works

Using Different Features of Signal in EMG Signal Classification

Turgunov, A., Zohirov, K., Rustamov, S., & Muhtorov, B. (2020) · International Conference on Information Science and Communications Technologies (ICISCT) · doi:10.1109/icisct50599.2020.9351392 · Cited by 17 · see citing works

A systematic approach to echocardiography in hypertrophic cardiomyopathy: a guideline protocol from the British Society of Echocardiography

Smith, N., Steeds, R. P., Masani, N. D., Sandoval, J., Wharton, G. A., Allen, J., Chambers, J. B., Jones, R. E., Lloyd, G., Rana, B. S., et al. (2015) · Echo Research and Practice · doi:10.1530/erp-14-0115 · Cited by 16 · see citing works

Localization and Classification of Myocardial Infarction Based on Artificial Neural Network

Muminov, B. B., Nasimov, R., Mirzakhalilov, S., Sayfullaeva, N., & Gadoyboeva, N. (2020) · Information Communication Technologies Conference (ICTC) · doi:10.1109/ictc49638.2020.9123300 · Cited by 15 · see citing works

Optimization of Identification of Images of Micro-Objects Taking Into Account Systematic Error Based on Neural Networks

Ibragimovich, J. I., Djumanov, O. I., & Abdullayevich, S. R. (2020) · International Russian Automation Conference (RusAutoCon) · doi:10.1109/rusautocon49822.2020.9208164 · Cited by 15 · see citing works

A new dataset for the detection of hand movements based on the SEMG signal

Turgunov, A., Zohirov, K., & Muhtorov, B. (2020) · IEEE International Conference on Application of Information and Communication Technologies (AICT) · doi:10.1109/aict50176.2020.9368735 · Cited by 13 · see citing works

Algorithm of Automatic Differentiation of Myocardial Infarction from Cardiomyopathy based on Electrocardiogram

Nasimov, R., Muminov, B. B., Mirzakhalilov, S., & Nasimova, N. (2020) · IEEE International Conference on Application of Information and Communication Technologies (AICT) · doi:10.1109/aict50176.2020.9368738 · Cited by 12 · see citing works

GAN-enhanced Conditional Echocardiogram GenerationPreprint

Abdi, A. H., Tsang, T. S. M., & Abolmaesumi, P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1911.02121 · Cited by 6 · see citing works

Development of the Method, Algorithm and Software of a Modern Non-invasive Biopotential Meter System

Djumanov, J. X., Rajabov, F., Тургунбаевна, А. К., Tadjibaeva, D. A., & Atadjanova, N. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-68449-5_10 · Cited by 6 · see citing works

IDEF Models And Innovative System For Search Data In Stochastic Information Environment

Muminov, B. B., & Bekmurodov, U. B. (2020) · IEEE International Conference on Application of Information and Communication Technologies (AICT) · doi:10.1109/aict50176.2020.9368581 · Cited by 6 · see citing works

A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis

Xu, X., Li, J., Zhu, Z., Zhao, L., Wang, H., Song, C., Chen, Y., Zhao, Q., Yang, J., & Pei, Y. (2024) · Bioengineering · doi:10.3390/bioengineering11030219 · Cited by 242 · see citing works

Evaluating Synthetic Medical Images Using Artificial Intelligence with the GAN Algorithm

Abdusalomov, A. B., Nasimov, R., Nasimova, N., Muminov, B. B., & Whangbo, T. K. (2023) · Sensors · doi:10.3390/s23073440 · Cited by 62 · see citing works

Recent advancements and applications of deep learning in heart failure: Α systematic review

Πετμεζάς, Γ., Papageorgiou, V. Ε., Vassilikos, V. P., Pagourelias, E. D., Tsaklidis, G. M., Katsaggelos, A. K., & Maglaveras, N. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108557 · Cited by 50 · see citing works

Deep learning supported echocardiogram analysis: A comprehensive review

Sanjeevi, G., Gopalakrishnan, U., Pathinarupothi, R. K., & Madathil, T. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102866 · Cited by 15 · see citing works

Hybrid Method for Evaluating Feature Importance for Predicting Chronic Heart Diseases

Nasimov, R., Nasimova, N., & Muminov, B. B. (2022) · International Conference on Information Science and Communications Technologies (ICISCT) · doi:10.1109/icisct55600.2022.10146969 · Cited by 12 · see citing works

Deep Learning Algorithm for Classifying Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy in Transport Workers

Nasimov, R., Nasimova, N., Karimov, B., & Abdullayev, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-30258-9_19 · Cited by 10 · see citing works

Generating and Evaluating Synthetic Medical Images

Nasimova, N., Nasimov, R., Sobirova, G., Usmanxodjayeva, A., Rakhimov, M., & Javliev, S. (2024) · International Conference on Information Science and Communications Technologies (ICISCT) · doi:10.1109/icisct64202.2024.10957704 · Cited by 9 · see citing works

Speech Recognition Technologies Based on Artificial Intelligence Algorithms

Musaev, M., Khujayorov, I., & Ochilov, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-27199-1_6 · Cited by 9 · see citing works

Clinical course of adults with co-occurring hypertrophic cardiomyopathy and hypertension: A scoping review

Arabadjian, M. E., Montgomery, S., Pleasure, M., Nicolas, B., Collins, M., Reuter, M., Massera, D., Shimbo, D., & Sherrid, M. V. (2024) · American Heart Journal Plus Cardiology Research and Practice · doi:10.1016/j.ahjo.2024.100367 · Cited by 6 · see citing works

HCM-Dynamic-Echo: A Framework for Detecting Hypertrophic Cardiomyopathy (HCM) in Echocardiograms

Almadani, A., Agu, E., Sarwar, A., Ahluwalia, M., & Kpodonu, J. (2023) · 2023 IEEE International Conference on Digital Health (ICDH) · doi:10.1109/icdh60066.2023.00039 · Cited by 5 · see citing works

Differential diagnosis between dilated cardiomyopathy and ischemic cardiomyopathy based on variational mode decomposition and high order spectra analysis

Han, Y., Zhao, Y., Lin, Z., Liang, Z., Chen, S., & Zhang, J. (2023) · Health Information Science and Systems · doi:10.1007/s13755-023-00244-9 · Cited by 3 · see citing works

Visual-Sensory Information Processing Using Multichannel EEG Signals

Тургунбаевна, А. К., Rajabov, F., Karimova, N., & Akbarova, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53827-8_7 · Cited by 3 · see citing works

Creation of a Multi-Functional Device for Real-Time Monitoring of Water Quality

Rajabov, F., Jamoljon, D., Тургунбаевна, А. К., & Jamolov, K. (2025) · Springer proceedings in mathematics & statistics · doi:10.1007/978-3-031-85926-7_13 · Cited by 3 · see citing works

Generation and evaluation of synthetic digital medical images using artificial intelligence

Muminov, B., Nasimova, N., & Nasimov, R. (2022) · doi:10.55439/eit/vol10_iss3/a34

Satellite Imagery Super Resolution Using Classical and Deep Learning Algorithms

Ataxonovich, K. T., Djumanov, J. X., Ochilov, T., & Sabitova, N. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-53830-8_8

Automated identification of left ventricular hypertrophy using cardiac ultrasound imaging: A systematic review of artificial intelligence driven approaches

James, J., Gudigar, A., Raghavendra, U., Samanth, J., Maithri, M., Kaprekar, A., Prabhu, M. A., Salvi, M., Molinari, F., Ciaccio, E. J., et al. (2025) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2025.101730

A Hybrid Algorithm for Constructing an Optimized Set of Informative Features

Zohirov, K., Nasimov, R., Mukhammedieva, D., Klicheva, F., Sherboboyeva, G., & Boykobilov, S. (2025) · International Conference on Future Networks and Distributed Systems (ICFNDS) · doi:10.1145/3789692.3789790

Deep Learning Algorithm for Classifying Dilated Cardiomyopathy and Hypertrophic Cardiomyopathy in Transport Workers

Nasimov, R., Nasimova, N., Karimov, B., & Abdullayev, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-30258-9_19 · Cited by 10 · see citing works

Detection and diagnosis of dilated cardiomyopathy and hypertrophic cardiomyopathy using image processing techniques

Balaji, N., Subashini, T. S., & Chidambaram, N. (2016) · Engineering Science and Technology an International Journal · doi:10.1016/j.jestch.2016.10.001 · Cited by 29 · see citing works

Echocardiography-based machine learning algorithm for distinguishing ischemic cardiomyopathy from dilated cardiomyopathy

Zhou, M. L., Deng, Y., Liu, Y., Su, X., & Zeng, X. (2023) · BMC Cardiovascular Disorders · doi:10.1186/s12872-023-03520-4 · Cited by 24 · see citing works

Detection and Diagnosis of Dilated and Hypertrophic Cardiomyopathy by Echocardiogram Sequences Analysis

Balaji, N., Subashini, T. S., Chidambaram, N., & Balasubramaiyan, E. (2015) · Advances in intelligent systems and computing · doi:10.1007/978-981-10-0251-9_28 · Cited by 4 · see citing works

Improving Early Cardiomyopathy Diagnosis with CNNs: A Deep Learning-Based Approach

Abinaya, M., Duvvuri, S. K., J, S. K. P., Surendran, R., & Balamurugan, K. S. (2025) · International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech) · doi:10.1109/iementech65115.2025.10959655 · Cited by 5 · see citing works