Machine learning for the diagnosis of Parkinson's disease: a review of literature
Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and
assessment of clinical signs, including the characterization of a variety of motor symptoms …
assessment of clinical signs, including the characterization of a variety of motor symptoms …
A brief review on multi-task learning
KH Thung, CY Wee - Multimedia Tools and Applications, 2018 - Springer
Abstract Multi-task learning (MTL), which optimizes multiple related learning tasks at the
same time, has been widely used in various applications, including natural language …
same time, has been widely used in various applications, including natural language …
Classification of monkeypox images based on transfer learning and the Al-Biruni Earth Radius Optimization algorithm
The world is still trying to recover from the devastation caused by the wide spread of COVID-
19, and now the monkeypox virus threatens becoming a worldwide pandemic. Although the …
19, and now the monkeypox virus threatens becoming a worldwide pandemic. Although the …
Meta-heuristic optimization of LSTM-based deep network for boosting the prediction of monkeypox cases
Recent technologies such as artificial intelligence, machine learning, and big data are
essential for supporting healthcare monitoring systems, particularly for monitoring …
essential for supporting healthcare monitoring systems, particularly for monitoring …
Disease prediction using graph convolutional networks: application to autism spectrum disorder and Alzheimer's disease
Graphs are widely used as a natural framework that captures interactions between
individual elements represented as nodes in a graph. In medical applications, specifically …
individual elements represented as nodes in a graph. In medical applications, specifically …
Detecting the stages of Alzheimer's disease with pre-trained deep learning architectures
S Savaş - Arabian Journal for Science and Engineering, 2022 - Springer
Deep learning algorithms have begun to be used in medical image processing studies,
especially in the last decade. MRI is used in the diagnosis of Alzheimer's disease, a type of …
especially in the last decade. MRI is used in the diagnosis of Alzheimer's disease, a type of …
The heterophilic graph learning handbook: Benchmarks, models, theoretical analysis, applications and challenges
Homophily principle,\ie {} nodes with the same labels or similar attributes are more likely to
be connected, has been commonly believed to be the main reason for the superiority of …
be connected, has been commonly believed to be the main reason for the superiority of …
Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease
J Zhang - npj Parkinson's Disease, 2022 - nature.com
Parkinson's disease (PD) is a common, progressive, and currently incurable
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …
A systematic literature review on multimodal machine learning: Applications, challenges, gaps and future directions
Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
heterogeneous data from multiple modalities and machine learning (ML) are combined to …
Deep learning-based classification of healthy aging controls, mild cognitive impairment and Alzheimer's disease using fusion of MRI-PET imaging
VPS Rallabandi, K Seetharaman - Biomedical Signal Processing and …, 2023 - Elsevier
Automated detection of dementia stage using multimodal imaging modalities will be helpful
for improving the clinical diagnosis. In this study, we develop the Inception-ResNet wrapper …
for improving the clinical diagnosis. In this study, we develop the Inception-ResNet wrapper …