Haipeng Liu

Haipeng Liu received his Bachelor and Master in Engineering degrees from Zhejiang University, China, in 2012 and 2015, respectively, and Doctor of Philosophy in Medical Sciences from the Chinese University of Hong Kong, in 2018. From 2019 to 2020, he was a research fellow with the Medical Technology Research Center, Anglia Ruskin University. Since 2020, he has been a research fellow with Coventry University, UK. He is the author of over 60 journal articles and 10 conference papers. His research interests include biomechanics, physiological measurement, and computational simulation of cardiovascular diseases.

Publications

Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems
Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems
Haipeng Liu, Rajesh Kumar Tripathy, Pronaya Bhattacharya. © 2024. 300 pages.
As the demand for advanced technologies to revolutionize patient care intensifies, the medical industry faces a pressing need to confront challenges hindering the assimilation of...
Intelligent Biosensors for Healthcare 5.0
Intelligent Biosensors for Healthcare 5.0
Lihang Zhu, Jucheng Zhang, Haipeng Liu, Yonghua Chu. © 2024. 17 pages.
Increasing demands for smart health management driven by aging population and chronic diseases are transforming traditional healthcare delivery into intelligent and personalized...
Recent Applications of Convolutional Neural Networks in Medical Data Analysis
Recent Applications of Convolutional Neural Networks in Medical Data Analysis
Ling Dai, Mingming Zhou, Haipeng Liu. © 2024. 13 pages.
Cutting-edge artificial intelligence techniques especially deep learning algorithms have shown great potentials in data-driven diagnostics. Convolutional neural networks (CNNs)...
Functional Magnetic Resonance Imaging: An Overview of Technical Advances and Clinical Applications
Functional Magnetic Resonance Imaging: An Overview of Technical Advances and Clinical Applications
Lumeng Zhang, Xinhong Wang, Haipeng Liu. © 2024. 21 pages.
Functional magnetic resonance imaging (fMRI), with its unique advantages of non-invasiveness, relatively balanced spatial and temporal resolution, repeatability, and whole brain...
Automatic Diagnosis of Parkinson's Disease Based on Deep Learning Models and Multimodal Data
Automatic Diagnosis of Parkinson's Disease Based on Deep Learning Models and Multimodal Data
Ling Li, Fangyu Dai, Songbin He, Hao Yu, Haipeng Liu. © 2024. 22 pages.
Parkinson's disease (PD) is a common age-related neurodegenerative disorder in the aging society. Early diagnosis of PD is particularly important for efficient intervention....
Emerging MRI Techniques in Clinical Practice of Cerebrovascular Diseases
Emerging MRI Techniques in Clinical Practice of Cerebrovascular Diseases
Haipeng Liu, Linlin Ma, Mengxi Xu, Xinhong Wang. © 2024. 19 pages.
Magnetic resonance imaging (MRI) is a non-invasive imaging technique without ionizing radiation. Nowadays, MRI plays an irreplaceable role in neuroscience research and the...
Applications of Magnetic Resonance Imaging in Stroke for Multidimensional Assessment
Applications of Magnetic Resonance Imaging in Stroke for Multidimensional Assessment
Xinhong Wang, Haipeng Liu. © 2023. 16 pages.
Stroke remains a leading cause of disability and death worldwide. Accurate diagnosis of stroke is vital for guiding treatment decisions and predicting outcomes. Different types...