Medical experts are utilizing neuroimaging and clinical assessments to enhance the early identification of Parkinson's disease. The current research initiative offers ways to identify Parkinson's disease using...
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Medical experts are utilizing neuroimaging and clinical assessments to enhance the early identification of Parkinson's disease. The current research initiative offers ways to identify Parkinson's disease using machine learning and transfer learning. To carry out this, we extracted 7500 MRI images from 2022 and 2023 and 12 clinical assessment records from 2010 to 2023 from the well-known Parkinson's Progression Marker Initiative (PPMI) database. Then, we applied machine and transfer learning approaches using clinical assessment records and MRI images, respectively. To identify Parkinson's Disease (PD) using samples from clinical assessments, four distinct resampling techniques were employed. Subsequently, three machine learning models were applied to train on these resample records, and the recall score was analyzed. A hybrid of SMOTE and ENN proved to be the most effective approach for handling all of the imbalanced data, according to the recall study. Later, four different feature selection methods were used to find the top 10 features using these new samples. Lastly, we trained and validated the model using nine machine-learning algorithms. We also used explainable AI techniques like LIME and SHAP to interpret clinical assessment records. The extra tree classifier outperformed the others in terms of accuracy, reaching 98.44% using the tree-based feature selection technique. In addition to examining clinical assessment samples, this study investigated Parkinson's disease using neuroimaging data. In pursuit of this objective, four pre-trained architectures were employed to analyze MRI images through two distinct approaches. The first approach involved utilizing the convolutional layer while replacing the remaining two layers with a customized Artificial Neural Network (ANN). Subsequently, training and evaluation are performed using our MRI samples, followed by analyzing significant weights using a LIME interpretable explainer. The second approach employs an improvis
Image inpainting has made great achievements recently, but it is often tough to generate a semantically consistent image when faced with large missing areas in complex scenes. To address semantic and structural alignm...
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Background: The synthesis of reversible logic has gained prominence as a crucial research area, particularly in the context of post-CMOS computing devices, notably quantum computing. Objective: To implement the bitoni...
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作者：
Shim, HyungboASRI
Electrical and Computer Engineering Department Seoul National University Korea Republic of
A swarm of individuals often exhibits behaviors that are not possible for each individual. This phenomenon is called emergence, and this paper mathematically demonstrates that new dynamics can arise in swarm behavior ...
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Bidirectional interlinking converter(BIC)is the core equipment in a hybrid AC/DC microgrid connected between AC and DC ***,the variety of control modes and flexible bidirectional power flow complicate the influence of...
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Bidirectional interlinking converter(BIC)is the core equipment in a hybrid AC/DC microgrid connected between AC and DC ***,the variety of control modes and flexible bidirectional power flow complicate the influence of AC faults on BIC itself and on DC sub-grid,which potentially threaten both converter safety and system *** study first investigates AC fault influence on the BIC and DC bus voltage under different BIC control modes and different pre-fault operation states,by developing a mathematical model and equivalent sequence ***,based on the analysis results,a general accommodative current limiting strategy is proposed for BIC without limitations to specific mode or operation *** amplitude is predicted and constrained according to the critical requirements to protect the BIC and relieving the AC fault influence on the DC bus *** with conventional methods,potential current limit failure and distortions under asymmetric faults can also be ***,experiments verify feasibility of the proposed method.
This paper introduces a methodology for parameterizing the DER A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The ...
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We propose a new method called the Metropolis-adjusted Mirror Langevin algorithm for approximate sampling from distributions whose support is a compact and convex set. This algorithm adds an accept-reject filter to th...
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Background: Pneumonia is one of the leading causes of death and disability due to respiratory infections. The key to successful treatment of pneumonia is in its early diagnosis and correct classification. PneumoniaNet...
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Pretrained language models leverage selfsupervised learning to use large amounts of unlabeled text for learning contextual representations of sequences. However, in the domain of medical conversations, the availabilit...
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This work proposes a distributed estimation and control approach in which a team of aerial agents equipped with radio jamming devices collaborate in order to intercept and concurrently track-and-jam a malicious target...
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