Graph-based deep learning for medical diagnosis and analysis: past, present and future

D Ahmedt-Aristizabal, MA Armin, S Denman, C Fookes… - Sensors, 2021 - mdpi.com
With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

[HTML][HTML] Automatic two-dimensional & three-dimensional video analysis with deep learning for movement disorders: A systematic review

W Tang, PMA van Ooijen, DA Sival… - Artificial Intelligence in …, 2024 - Elsevier
The advent of computer vision technology and increased usage of video cameras in clinical
settings have facilitated advancements in movement disorder analysis. This review …

Causality-driven graph neural network for early diagnosis of pancreatic cancer in non-contrast computerized tomography

X Li, R Guo, J Lu, T Chen, X Qian - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Pancreatic cancer is the emperor of all cancer maladies, mainly because there are no
characteristic symptoms in the early stages, resulting in the absence of effective screening …

[HTML][HTML] WiFOG: Integrating deep learning and hybrid feature selection for accurate freezing of gait detection

Z Habib, MA Mughal, MA Khan, M Shabaz - Alexandria Engineering …, 2024 - Elsevier
This study investigates the feasibility of utilizing non-invasive WiFi sensing using the 4.8
GHz operating frequency band of the 5 G spectrum, which is suitable for Internet of Things …

A tree-structure-guided graph convolutional network with contrastive learning for the assessment of parkinsonian hand movements

R Guo, H Li, C Zhang, X Qian - Medical Image Analysis, 2022 - Elsevier
Bradykinesia is one of the core motor symptoms of Parkinson's disease (PD). Neurologists
typically perform face-to-face bradykinesia assessment in PD patients according to the …

Automatic labeling of Parkinson's Disease gait videos with weak supervision

M Gholami, R Ward, R Mahal, M Mirian, K Yen… - Medical Image …, 2023 - Elsevier
Motor dysfunction in Parkinson's Disease (PD) patients is typically assessed by clinicians
employing the Movement Disorder Society's Unified Parkinson's Disease Rating Scale …

Video-based quantification of gait impairments in Parkinson's disease using skeleton-silhouette fusion convolution network

Q Zeng, P Liu, N Yu, J Wu, W Huo… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Gait impairments are among the most common hallmarks of Parkinson's disease (PD),
usually appearing in the early stage and becoming a major cause of disability with disease …

An fNIRS-based dynamic functional connectivity analysis method to signify functional neurodegeneration of Parkinson's disease

J Lu, X Zhang, Y Wang, Y Cheng, Z Shu… - … on Neural Systems …, 2023 - ieeexplore.ieee.org
Parkinson's disease (PD) is a prevalent brain disorder, and PD diagnosis is crucial for
treatment. Existing methods for PD diagnosis are mainly focused on behavior analysis, while …

A causal counterfactual graph neural network for arising-from-chair abnormality detection in parkinsonians

X Tang, R Guo, C Zhang, X Qian - Medical Image Analysis, 2024 - Elsevier
The arising-from-chair task assessment is a key aspect of the evaluation of movement
disorders in Parkinson's disease (PD). However, common scale-based clinical assessment …

Cross-Spatiotemporal Graph Convolution Networks for Skeleton-Based Parkinsonian Gait MDS-UPDRS Score Estimation

H Tian, H Li, W Jiang, X Ma, X Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Gait impairment in Parkinson's Disease (PD) is quantitatively assessed using the Movement
Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), a well …