A5021051118- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Advanced Neuroimaging Techniques and Applications
- Sports Performance and Training
- Artificial Intelligence in Healthcare and Education
- Muscle activation and electromyography studies
- Fetal and Pediatric Neurological Disorders
- High-Velocity Impact and Material Behavior
- Rock Mechanics and Modeling
- Non-Invasive Vital Sign Monitoring
- Advanced X-ray and CT Imaging
- Advanced Radiotherapy Techniques
- Traumatic Brain Injury and Neurovascular Disturbances
- Advanced MRI Techniques and Applications
- Winter Sports Injuries and Performance
- Cerebrospinal fluid and hydrocephalus
- Medical Imaging Techniques and Applications
- Phytochemistry and Biological Activities
- Brain Tumor Detection and Classification
- Heart Rate Variability and Autonomic Control
- Lower Extremity Biomechanics and Pathologies
- Advanced Fiber Optic Sensors
- Glioma Diagnosis and Treatment
- Machine Learning in Healthcare
- Andrographolide Research and Applications
University of Auckland
2023-2025
Chinese PLA General Hospital
2024
Brain Research New Zealand
2024
Loma Linda University
2008
Johns Hopkins University
1987
Abstract Purpose To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research of radiomics studies. Methods We conducted an online modified Delphi study with group international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members identify the items be voted; Stage#3, four rounds exercise by panelists determine eligible for METRICS their weights. The...
BackgroundHeart rate, as the four vital signs of human body, is a basic indicator to measure person's health status. Traditional electrocardiography (ECG) measurement, which routinely monitored, requires subjects wear lead electrodes frequently, undoubtedly places great restrictions on participants' activities during normal test. At present, boom wearable devices has created hope for non-invasive, simple operation and low-cost daily heart rate monitoring, among them, Ballistocardiogram...
<h3>Background:</h3> In recent years, the deployment of sophisticated technological solutions in medical domain has garnered increasing interest. Through lens Artificial Intelligence (AI), field stands on cusp a significant paradigm shift, one that holds promise elevating healthcare delivery to pinnacle excellence, driven by synergy between human expertise and machine intelligence. <h3>Objectives:</h3> This research aims develop stringent evaluation criterion for assessing large language...
Averaging is commonly used for data reduction/aggregation to summarise such high-dimensional data, resulting in information loss. However, individual variability makes group-wise comparisons difficult without reduction/aggregation. To address these issues, we developed a novel technique that integrates diffusion tensor (DTI) metrics along the whole volumes of fibre bundle using mesh-fitting technique. Using right Corticospinal Tract (rCST) as an example, demonstrate utility method detecting...
The rapid advancement of technology has brought significant changes to various fields, including medical imaging (MI). This discussion paper explores the integration computing technologies (e.g. Python and MATLAB), digital image processing enhancement, segmentation three-dimensional reconstruction) artificial intelligence (AI) into undergraduate MI curriculum. By examining current educational practices, gaps limitations that hinder development future-ready professionals are identified. A...