4003. Biomedical engineering
| Title | 4003. Biomedical engineering |
|---|---|
| Parent | 40. Engineering |
Latest research outputs
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Automated recognition of major depressive disorder from cardiovascular and respiratory physiological signals
Zitouni, M. Sami, Oh, Shu Li, Vicnesh, Jahmunah, Khandoker, Ahsan and Acharya, U. Rajendra. 2022. "Automated recognition of major depressive disorder from cardiovascular and respiratory physiological signals." Frontiers in Psychiatry. 13. https://doi.org/10.3389/fpsyt.2022.970993Article
Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques
Vidhya, V, Raghavendra, U., Gudigar, Anjan, Kasula, Praneet, Chakole, Yashas, Hegde, Ajay, Menon, Girish, Ooi, Chui Ping, Ciaccio, Edward J. and Acharya, U. Rajendra. 2022. "Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques." Informatics. 9 (1). https://doi.org/10.3390/informatics9010004Article
Use of Differential Entropy for Automated Emotion Recognition in a Virtual Reality Environment with EEG Signals
Uyanık, Hakan, Ozcelik, Salih Taha A., Duranay, Zeynep Bala Duranay, Sengur, Abdulkadir and Acharya, U. Rajendra. 2022. "Use of Differential Entropy for Automated Emotion Recognition in a Virtual Reality Environment with EEG Signals." Diagnostics. 12 (10). https://doi.org/10.3390/diagnostics12102508Article
Tetromino pattern based accurate EEG emotion classification model
Tuncer, Turker, Dogan, Sengul, Baygin, Mehmet and Acharya, U. Rajendra. 2022. "Tetromino pattern based accurate EEG emotion classification model." Artificial Intelligence in Medicine. 123. https://doi.org/10.1016/j.artmed.2021.102210Article
Development of accurate automated language identification model using polymer pattern and tent maximum absolute pooling techniques
Tuncer, Turker, Dogan, Sengul, Akbal, Erhan, Cicekli, Abdullah and Acharya, U. Rajendra. 2022. "Development of accurate automated language identification model using polymer pattern and tent maximum absolute pooling techniques." Neural Computing and Applications. 34 (6), pp. 4875-4888. https://doi.org/10.1007/s00521-021-06678-0Article
Assessment of CT for the categorization of hemorrhagic stroke (HS) and cerebral amyloid angiopathy hemorrhage (CAAH): A review
Sudarshan, Vidya K., Raghavendra, U., Gudigar, Anjan, Ciaccio, Edward J., Vijayananthan, Anushya, Sahathevan, Ramesh and Acharya, U. Rajendra. 2022. "Assessment of CT for the categorization of hemorrhagic stroke (HS) and cerebral amyloid angiopathy hemorrhage (CAAH): A review." Biocybernetics and Biomedical Engineering. 42 (3), pp. 888-901. https://doi.org/10.1016/j.bbe.2022.07.001Article
Attention-based 3D CNN with residual connections for efficient ECG-based COVID-19 detection
Sobahi, Nebras, Sengur, Abdulkadir, Tan, Ru-San and Acharya, U. Rajendra. 2022. "Attention-based 3D CNN with residual connections for efficient ECG-based COVID-19 detection." Computers in Biology and Medicine. 143. https://doi.org/10.1016/j.compbiomed.2022.105335Article
Explainable COVID-19 detection using fractal dimension and vision transformer with Grad-CAM on cough sounds
Sobahi, Nebras, Atila, Orhan, Deniz, Erkan, Sengur, Abdulkadir and Acharya, U. Rajendra. 2022. "Explainable COVID-19 detection using fractal dimension and vision transformer with Grad-CAM on cough sounds." Biocybernetics and Biomedical Engineering. 42 (3), pp. 1066-1080. https://doi.org/10.1016/j.bbe.2022.08.005Article
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works
Shoeibi, Afshin, Moridian, Parisa, Khodatars, Marjane, Ghassemi, Navid, Jafari, Mahboobeh, Alizadehsani, Roohallah, Kong, Yinan, Gorriz, Juan Manuel, Ramírez, Javier, Khosravi, Abbas, Nahavandi, Saeid and Acharya, U. Rajendra. 2022. "An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works." Computers in Biology and Medicine. 149. https://doi.org/10.1016/j.compbiomed.2022.106053Article
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
Shoeibi, Afshin, Ghassemi, Navid, Khodatars, Marjane, Moridian, Parisa, Alizadehsani, Roohallah, Zare, Assef, Khosravi, Abbas, Subasi, Abdulhamit, Acharya, U. Rajendra and Gorriz, Juan M.. 2022. "Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies." Biomedical Signal Processing and Control. 73. https://doi.org/10.1016/j.bspc.2021.103417Article
An Automated Wavelet-Based Sleep Scoring Model Using EEG, EMG, and EOG Signals with More than 8000 Subjects
Sharma, Manish, Yadav, Anuj, Tiwari, Jainendra, Karabatak, Murat, Yildirim, Ozal and Acharya, U. Rajendra. 2022. "An Automated Wavelet-Based Sleep Scoring Model Using EEG, EMG, and EOG Signals with More than 8000 Subjects." International Journal of Environmental Research and Public Health. 19 (12). https://doi.org/10.3390/ijerph19127176Article
Automated detection of obstructive sleep apnea in more than 8000 subjects using frequency optimized orthogonal wavelet filter bank with respiratory and oximetry signals
Sharma, Manish, Kumbhani, Divyash, Tiwari, Jainendra, Kumar, T. Sudheer and Acharya, U. Rajendra. 2022. "Automated detection of obstructive sleep apnea in more than 8000 subjects using frequency optimized orthogonal wavelet filter bank with respiratory and oximetry signals." Computers in Biology and Medicine. 144. https://doi.org/10.1016/j.compbiomed.2022.105364Article
Pulse oximetry SpO 2 signal for automated identification of sleep apnea: a review and future trends
Sharma, Manish, Kumar, Kamlesh, Kumar, Prince, Tan, Ru-San and Acharya, U Rajendra. 2022. "Pulse oximetry SpO 2 signal for automated identification of sleep apnea: a review and future trends." Physiological Measurement. 43 (11). https://doi.org/10.1088/1361-6579/ac98f0Article
Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals
Sharma, Manish, Darji, Jay, Thakrar, Madhav and Acharya, U. Rajendra. 2022. "Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals." Computers in Biology and Medicine. 143. https://doi.org/10.1016/j.compbiomed.2022.105224Article
Automated sleep apnea detection in pregnant women using wavelet-based features
Sharma, Manish, Bapodara, Sagar, Tiwari, Jainendra and Acharya, U. Rajendra. 2022. "Automated sleep apnea detection in pregnant women using wavelet-based features." Informatics in Medicine Unlocked. 32. https://doi.org/10.1016/j.imu.2022.101026Article
MCUa: Multi-Level Context and Uncertainty Aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification
Senousy, Zakaria, Abdelsamea, Mohammed M., Gaber, Mohamed Medhat, Abdar, Moloud, Acharya, U. Rajendra, Khosravi, Abbas and Nahavandi, Saeid. 2022. "MCUa: Multi-Level Context and Uncertainty Aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification." IEEE Transactions on Biomedical Engineering. 69 (2), pp. 818-829. https://doi.org/10.1109/TBME.2021.3107446Article
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works
Sadeghi, Delaram, Shoeibi, Afshin, Ghassemi, Navid, Moridian, Parisa, Khadem, Ali, Alizadehsani, Roohallah, Teshnehlab, Mohammad, Gorriz, Juan M., Khozeimeh, Fahime, Zhang, Yu-Dong, Nahavandi, Saeid and Acharya, U. Rajendra. 2022. "An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works." Computers in Biology and Medicine. 146. https://doi.org/10.1016/j.compbiomed.2022.105554Article
Electrochemical Biosensing and Deep Learning-Based Approaches in the Diagnosis of COVID-19: A Review
Sadak, Omer, Sadak, Ferhat, Yildirim, Ozal, Iverson, Nicole M., Qureshi, Rizwan, Talo, Muhammed, Ooi, Chui Ping, Acharya, U. Rajendra, Gunasekaran, Sundaram and Alam, Tanvir. 2022. "Electrochemical Biosensing and Deep Learning-Based Approaches in the Diagnosis of COVID-19: A Review." IEEE Access. 10, pp. 98633-98648. https://doi.org/10.1109/ACCESS.2022.3207207Article
Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images
Rao, B. Nageswara, Mohanty, Sudhansu, Sen, Kamal, Acharya, U. Rajendra, Cheong, Kang Hao and Sabut, Sukanta. 2022. "Deep Transfer Learning for Automatic Prediction of Hemorrhagic Stroke on CT Images." Computational and Mathematical Methods in Medicine. 2022. https://doi.org/10.1155/2022/3560507Article
Automated Detection of Hypertension Using Continuous Wavelet Transform and a Deep Neural Network with Ballistocardiography Signals
Rajput, Jaypal Singh, Sharma, Manish, Kumar, T. Sudheer and Acharya, U. Rajendra. 2022. "Automated Detection of Hypertension Using Continuous Wavelet Transform and a Deep Neural Network with Ballistocardiography Signals." International Journal of Environmental Research and Public Health. 19 (7). https://doi.org/10.3390/ijerph19074014Article
Feature-versus deep learning-based approaches for the automated detection of brain tumor with magnetic resonance images: A comparative study
Raghavendra, U., Gudigar, Anjan, Rao, Tejaswi N., Rajinikanth, V., Ciaccio, Edward J., Yeong, Chai Hong, Satapathy, S.C., Molinari, Filippo and Acharya, U. Rajendra. 2022. "Feature-versus deep learning-based approaches for the automated detection of brain tumor with magnetic resonance images: A comparative study." International Journal of Imaging Systems and Technology. 32 (2), pp. 501-516. https://doi.org/10.1002/ima.22646Article
Automated diagnosis of coronary artery disease using scalogram-based tensor decomposition with heart rate signals
Nesaragi, Naimahmed, Sharma, Ashish, Patidar, Shivnarayan and Acharya, U. Rajendra. 2022. "Automated diagnosis of coronary artery disease using scalogram-based tensor decomposition with heart rate signals." Medical Engineering and Physics. 110. https://doi.org/10.1016/j.medengphy.2022.103811Article
Application of artificial intelligence in wearable devices: Opportunities and challenges
Nahavandi, Darius, Alizadehsani, Roohallah, Khosravi, Abbas and Acharya, U. Rajendra. 2022. "Application of artificial intelligence in wearable devices: Opportunities and challenges." Computer Methods and Programs in Biomedicine. 213. https://doi.org/10.1016/j.cmpb.2021.106541Article
Automated classification of cyclic alternating pattern sleep phases in healthy and sleep-disordered subjects using convolutional neural network
Murarka, Shruti, Wadichar, Aditya, Bhurane, Ankit, Sharma, Manish and Acharya, U. Rajendra. 2022. "Automated classification of cyclic alternating pattern sleep phases in healthy and sleep-disordered subjects using convolutional neural network." Computers in Biology and Medicine. 146. https://doi.org/10.1016/j.compbiomed.2022.105594Article
Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
Moridian, Parisa, Ghassemi, Navid, Jafari, Mahboobeh, Salloum-Asfar, Salam, Sadeghi, Delar, Khodatars, Marjane, Shoeibi, Afshin, Khosravi, Abbas, Ling, Sai Ho, Subasi, Abdulhamit, Alizadehsani, Roohallah, Gorriz, Juan M., Abdulla, S.A. and Acharya, U. Rajendra. 2022. "Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review." Frontiers in Molecular Neuroscience. 15. https://doi.org/10.3389/fnmol.2022.999605Article
RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Moravvej, Seyed Vahid, Alizadehsani, Roohallah, Khanam, Sadia, Sobhaninia, Zahra, Shoeibi, Afshin, Khozeimeh, Fahime, Sani, Zahra Alizadeh, Tan, Ru-San, Khosravi, Abbas, Nahavandi, Saeid, Kadri, Nahrizul Adib, Azizan, Muhammad Mokhzaini, Arunkumar, N. and Acharya, U. Rajendra. 2022. "RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights." Contrast Media and Molecular Imaging. 2022. https://doi.org/10.1155/2022/8733632Article
Tumor Microenvironment, Radiology, and Artificial Intelligence: Should We Consider Tumor Periphery?
Mohammadi, A., Mirza-Aghazadeh-Attari, Mohammad, Faeghi, Fariborz, Homayoun, Hasan, Abolghasemi, Jamileh, Vogl, Thomas J., Bureau, Nathalie J., Bakhshandeh, Mohsen, Acharya, Rajendra U. and Ardakani, Ali Abbasian. 2022. "Tumor Microenvironment, Radiology, and Artificial Intelligence: Should We Consider Tumor Periphery?" Journal of Ultrasound in Medicine. 41 (12), pp. 3079-3090. https://doi.org/10.1002/jum.16086Article
Development of a Computational Tool for the Estimation of Alveolar Bone Loss in Oral Radiographic Images
Maithri, M., Balla, Dhanush G., Kumar, Santhosh, Raghavendra, U., Gudigar, Anjan, Chan, Wai Yee, Macherla, Shravya, Vineetha, Ravindranath, Gopalkrishna, Pratibha, Ciaccio, Edward J. and Acharya, U. Rajendra. 2022. "Development of a Computational Tool for the Estimation of Alveolar Bone Loss in Oral Radiographic Images." Computation. 10 (1). https://doi.org/10.3390/computation10010008Article
Transfer learning techniques for medical image analysis: A review
Kora, Padmavathi, Ooi, Chui Ping, Faust, Oliver, Raghavendra, U., Gudigar, Anjan, Chan, Wai Yee, Meenakshi, K., Swaraja, K., Plawiak, Pawel and Acharya, U. Rajendra. 2022. "Transfer learning techniques for medical image analysis: A review." Biocybernetics and Biomedical Engineering. 42 (1), pp. 79-107. https://doi.org/10.1016/j.bbe.2021.11.004Article
RF-CNN-F: random forest with convolutional neural network features for coronary artery disease diagnosis based on cardiac magnetic resonance
Khozeimeh, Fahime, Sharifrazi, Danial, Izadi, Navid Hoseini, Joloud, Javad Hassannataj, Shoeibi, Afshin, Alizadehsani, Roohallah, Tartibi, Mehrzad, Hussain, Sadiq, Sani, Zahra Alizadeh, Khodatars, Marjane, Sadeghi, Delaram, Khosravi, Abbas, Nahavandi, Saeid, Tan, Ru‑San, Acharya, U. Rajendra and Islam, Sheikh Mohammed Shariful. 2022. "RF-CNN-F: random forest with convolutional neural network features for coronary artery disease diagnosis based on cardiac magnetic resonance." Scientific Reports. 12 (1). https://doi.org/10.1038/s41598-022-15374-5Article
Multi-class nucleus detection and classification using deep convolutional neural network with enhanced high dimensional dissimilarity translation model on cervical cells
Karri, M., Annavarapu, Chandra Sekhara Rao, Mallik, Saurav, Zhao, Zhongming and Acharya, U. Rajendra. 2022. "Multi-class nucleus detection and classification using deep convolutional neural network with enhanced high dimensional dissimilarity translation model on cervical cells." Biocybernetics and Biomedical Engineering. 42 (3), pp. 797-814. https://doi.org/10.1016/j.bbe.2022.06.003Article
Explainable multi-module semantic guided attention based network for medical image segmentation
Karri, Meghana, Annavarapu, Chandra Sekhara Rao and Acharya, U. Rajendra. 2022. "Explainable multi-module semantic guided attention based network for medical image segmentation." Computers in Biology and Medicine. 151 (Part A). https://doi.org/10.1016/j.compbiomed.2022.106231Article
The internet of medical things and artificial intelligence: trends, challenges, and opportunities
Kakhi, Kourosh, Alizadehsani, Roohallah, Kabir, H.M. Dipu, Khosravi, Abbas, Nahavandi, Saeid and Acharya, U. Rajendra. 2022. "The internet of medical things and artificial intelligence: trends, challenges, and opportunities." Biocybernetics and Biomedical Engineering. 42 (3), pp. 749-771. https://doi.org/10.1016/j.bbe.2022.05.008Article
Aleatory-aware deep uncertainty quantification for transfer learning
Kabir, H M Dipu, Khanam, Sadia, Khozeimeh, Fahime, Khosravi, Abbas, Mondal, Subrota Kumar, Nahavandi, Saeid and Acharya, U. Rajendra. 2022. "Aleatory-aware deep uncertainty quantification for transfer learning." Computers in Biology and Medicine. 143. https://doi.org/10.1016/j.compbiomed.2022.105246Article
Applications of machine-learning algorithms for prediction of benign and malignant breast lesions using ultrasound radiomics signatures: A multi-center study
Homayoun, Hassan, Chan, Wai Yee, Kuzan, Taha Yusuf, Leong, Wai Ling, Altintoprak, Kübra Murzoglu, Mohammadi, Afshin, Vijayananthan, Anushya, Rahmat, Kartini, Leong, Sook Sam, Mirza-Aghazadeh-Attari, Mohammad, Ejtehadifar, Sajjad, Faeghi, Fariborz, Acharya, U. Rajendra and Ardakani, Ali Abbasian. 2022. "Applications of machine-learning algorithms for prediction of benign and malignant breast lesions using ultrasound radiomics signatures: A multi-center study." Biocybernetics and Biomedical Engineering. 42 (3), pp. 921-933. https://doi.org/10.1016/j.bbe.2022.07.004Article
Application of artificial intelligence techniques for automated detection of myocardial infarction: a review
Joloudari, Javad Hassannataj, Mojrian, Sanaz, Nodehi, Issa, Mashmool, Amir, Zadegan, Zeynab Kiani, Shirkharkolaie, Sahar Khanjani, Alizadehsani, Roohallah, Tamadon, Tahereh, Khosravi, Samiyeh, Kohnehshari, Mitra Akbari, Hassannatajjeloudari, Edris, Sharifrazi, Danial, Mosavi, Amir, Loh, Hui Wen, Tan, Ru-San and Acharya, U Rajendra. 2022. "Application of artificial intelligence techniques for automated detection of myocardial infarction: a review." Physiological Measurement. 43 (8). https://doi.org/10.1088/1361-6579/ac7fd9Article
Artificial intelligence, BI-RADS evaluation and morphometry: A novel combination to diagnose breast cancer using ultrasonography, results from multi-center cohorts
Hamyoon, Hessam, Chan, Wai Yee, Mohammadi, Afshin, Kuzan, Taha, Mirza-Aghazadeh-Attari, Mohammad, Leong, Wai Ling, Altintoprak, Kübra Murzoglu, Vijayananthan, Anushya, Rahmat, Kartini, Mumin, Nazimah Ab, Leong, Sook Sam, Ejtehadifar, Sajjad, Faeghi, Fariborz, Abolghasemi, Jamileh, Ciaccio, Edward J., Acharya, U. Rajendra and Ardakani, Ali Abbasian. 2022. "Artificial intelligence, BI-RADS evaluation and morphometry: A novel combination to diagnose breast cancer using ultrasonography, results from multi-center cohorts." European Journal of Radiology. 157. https://doi.org/10.1016/j.ejrad.2022.110591Article
Hyp-Net: Automated detection of hypertension using deep convolutional neural network and Gabor transform techniques with ballistocardiogram signals
Gupta, Kapil, Bajaj, Varun, Ansari, Irshad Ahmad and Acharya, U. Rajendra. 2022. "Hyp-Net: Automated detection of hypertension using deep convolutional neural network and Gabor transform techniques with ballistocardiogram signals." Biocybernetics and Biomedical Engineering. 42 (3), pp. 784-796. https://doi.org/10.1016/j.bbe.2022.06.001Article
Novel Hypertrophic Cardiomyopathy Diagnosis Index Using Deep Features and Local Directional Pattern Techniques
Gudigar, Anjan, Raghavendra, U., Samanth, Jyothi, Dharmik, Chinmay, Gangavarapu, Mokshagna Rohit, Nayak, Krishnananda, Ciaccio, Edward J., Tan, Ru-San, Molinari, Filippo and Acharya, U. Rajendra. 2022. "Novel Hypertrophic Cardiomyopathy Diagnosis Index Using Deep Features and Local Directional Pattern Techniques." Journal of Imaging. 8 (4). https://doi.org/10.3390/jimaging8040102Article
RESCOVIDTCNnet: A residual neural network-based framework for COVID-19 detection using TCN and EWT with chest X-ray images
El-Dahshan, El-Sayed. A, Bassiouni, Mahmoud. M, Hagag, Ahmed, Chakrabortty, Ripon K, Loh, Huiwen and Acharya, U.Rajendra. 2022. "RESCOVIDTCNnet: A residual neural network-based framework for COVID-19 detection using TCN and EWT with chest X-ray images." Expert Systems with Applications. 204. https://doi.org/10.1016/j.eswa.2022.117410Article