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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 …
The impact of artificial intelligence in the odyssey of rare diseases
Emerging machine learning (ML) technologies have the potential to significantly improve the
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …
research and treatment of rare diseases, which constitute a vast set of diseases that affect a …
Clinical impact of deep learning reconstruction in MRI
Deep learning has been recognized as a paradigm-shifting tool in radiology. Deep learning
reconstruction (DLR) has recently emerged as a technology used in the image …
reconstruction (DLR) has recently emerged as a technology used in the image …
A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review
Background Lung diseases, both infectious and non-infectious, are the most prevalent
cause of mortality overall in the world. Medical research has identified pneumonia, lung …
cause of mortality overall in the world. Medical research has identified pneumonia, lung …
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 …
Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network
Objectives To investigate whether a deep learning model can predict the bone mineral
density (BMD) of lumbar vertebrae from unenhanced abdominal computed tomography (CT) …
density (BMD) of lumbar vertebrae from unenhanced abdominal computed tomography (CT) …
[HTML][HTML] The role of neural network for the detection of Parkinson's disease: a sco** review
Background: Parkinson's Disease (PD) is a chronic neurodegenerative disorder that has
been ranked second after Alzheimer's disease worldwide. Early diagnosis of PD is crucial to …
been ranked second after Alzheimer's disease worldwide. Early diagnosis of PD is crucial to …
A comparative study: prediction of parkinson's disease using machine learning, deep learning and nature inspired algorithm
Parkinson's Disease (PD) is a degenerative and progressive neurological disorder worsens
over time. This disease initially affects people over 55 years old. Patients with PD often …
over time. This disease initially affects people over 55 years old. Patients with PD often …
Machine learning of schizophrenia detection with structural and functional neuroimaging
Schizophrenia (SZ) is a severe psychiatric illness, and it affects around 1% of the general
population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and …
population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and …
Covid-19 hierarchical classification using a deep learning multi-modal
Coronavirus disease 2019 (COVID-19), originating in China, has rapidly spread worldwide.
Physicians must examine infected patients and make timely decisions to isolate them …
Physicians must examine infected patients and make timely decisions to isolate them …