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Journal of Personalized Medicine
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February 23, 2024
Leveraging Machine Learning for Personalized Wearable Biomedical Devices: A Review
Ali Olyanasab, Mohsen Annabestani
Journal of Clinical Medicine
|
August 10, 2024
Application of Mixed/Augmented Reality in Interventional Cardiology
Mohsen Annabestani, Ali Olyanasab, Bobak Mosadegh
Scientific Reports
|
March 20, 2021
A 3D analytical ion transport model for ionic polymer metal composite actuators in large bending deformations
Mohsen Annabestani, Nadia Naghavi, Mohammad Maymandi-Nejad
Scientific Reports
|
October 6, 2020
A novel, low cost, and accessible method for rapid fabrication of the modifiable microfluidic devices
Mohsen Annabestani, Pouria Esmaeili-Dokht, Mehdi Fardmanesh
Research Square
|
June 4, 2026
Acoustic-based Stenosis Detection for Dialysis Patients using Explainable Machine Learning
Mohsen Annabestani, George Zhou, Herrick Wun, et al.
Scientific Reports
|
November 6, 2024
High-fidelity pose estimation for real-time extended reality (XR) visualization for cardiac catheterization
Mohsen Annabestani, Sandhya Sriram, Alexandre Caprio, et al.
Journal of Religion and Health
|
January 19, 2021
Correction to: How Resiliency and Hope Can Predict Stress of Covid-19 by Mediating Role of Spiritual Well-being Based on Machine Learning
Roghieh Nooripour, Simin Hosseinian, Abir Jaafar Hussain, et al.
Scientific Reports
|
November 28, 2022
A new 3D, microfluidic-oriented, multi-functional, and highly stretchable soft wearable sensor
Mohsen Annabestani, Pouria Esmaeili-Dokht, Ali Olyanasab, et al.
Micromachines
|
November 27, 2024
Design, Testing, and Validation of a Soft Robotic Sensor Array Integrated with Flexible Electronics for Mapping Cardiac Arrhythmias
Abdellatif Ait Lahcen, Michael Labib, Alexandre Caprio, et al.
Journal of Religion and Health
|
January 5, 2021
How Resiliency and Hope Can Predict Stress of Covid-19 by Mediating Role of Spiritual Well-being Based on Machine Learning
Roghieh Nooripour, Simin Hosseinian, Abir Jaafar Hussain, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
Journal of Personalized Medicine
|
February 23, 2024
Leveraging Machine Learning for Personalized Wearable Biomedical Devices: A Review
Ali Olyanasab, Mohsen Annabestani
Journal of Clinical Medicine
|
August 10, 2024
Application of Mixed/Augmented Reality in Interventional Cardiology
Mohsen Annabestani, Ali Olyanasab, Bobak Mosadegh
Scientific Reports
|
March 20, 2021
A 3D analytical ion transport model for ionic polymer metal composite actuators in large bending deformations
Mohsen Annabestani, Nadia Naghavi, Mohammad Maymandi-Nejad
Scientific Reports
|
October 6, 2020
A novel, low cost, and accessible method for rapid fabrication of the modifiable microfluidic devices
Mohsen Annabestani, Pouria Esmaeili-Dokht, Mehdi Fardmanesh
Research Square
|
June 4, 2026
Acoustic-based Stenosis Detection for Dialysis Patients using Explainable Machine Learning
Mohsen Annabestani, George Zhou, Herrick Wun, et al.
Scientific Reports
|
November 6, 2024
High-fidelity pose estimation for real-time extended reality (XR) visualization for cardiac catheterization
Mohsen Annabestani, Sandhya Sriram, Alexandre Caprio, et al.
Journal of Religion and Health
|
January 19, 2021
Correction to: How Resiliency and Hope Can Predict Stress of Covid-19 by Mediating Role of Spiritual Well-being Based on Machine Learning
Roghieh Nooripour, Simin Hosseinian, Abir Jaafar Hussain, et al.
Scientific Reports
|
November 28, 2022
A new 3D, microfluidic-oriented, multi-functional, and highly stretchable soft wearable sensor
Mohsen Annabestani, Pouria Esmaeili-Dokht, Ali Olyanasab, et al.
Micromachines
|
November 27, 2024
Design, Testing, and Validation of a Soft Robotic Sensor Array Integrated with Flexible Electronics for Mapping Cardiac Arrhythmias
Abdellatif Ait Lahcen, Michael Labib, Alexandre Caprio, et al.
Journal of Religion and Health
|
January 5, 2021
How Resiliency and Hope Can Predict Stress of Covid-19 by Mediating Role of Spiritual Well-being Based on Machine Learning
Roghieh Nooripour, Simin Hosseinian, Abir Jaafar Hussain, et al.
Page
of 1