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
This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel *** plate remains stationary,while the other moves downward at a squeezing *** space bet...
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This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel *** plate remains stationary,while the other moves downward at a squeezing *** space between these plates contains a Darcy-Forchheimer porous medium.A mixture of water-based fluid with gold(Au)and silicon dioxide(Si O2)nanoparticles is *** contrast to the conventional Fourier's heat flux equation,this study employs the Cattaneo-Christov heat flux equation.A uniform magnetic field is applied perpendicular to the flow direction,invoking magnetohydrodynamic(MHD)***,the model accounts for Joule heating,which is the heat generated when an electric current passes through the *** problem is solved via NDSolve in *** and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow,energy transport,and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management *** is observed that the squeezing motion generates additional pressure gradients within the fluid,which enhances the flow rate but reduces the frictional ***,the fluid is pushed more vigorously between the plates,increasing the flow *** the fluid experiences higher flow rates due to the increased squeezing effect,it spends less time in the region between the *** thermal relaxation,however,abruptly changes the temperature,leading to a decrease in the temperature fluctuations.
Time series anomaly detection is a technology that finds outliers in observed data over time, and is a significant research field associated with many applications or platforms. In this paper, we propose a method call...
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The paper proposed a secured and efficient data aggregation mechanism leveraging the edge computing paradigm and homomorphic data encryption technique. The paper used a unique combination of Paillier cryptosystem and ...
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Plant disease causes a highly significant impact on production due to its destructive characteristics. A variety of chemical techniques should be applied to agriculture at different stages of disease infestation to en...
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Off-axis digital holography plays a crucial role in high-precision three-dimensional imaging. However, high-resolution phase images are often affected by the limited pixel size of the sensor. To address this issue, th...
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In this paper we consider the motion planning problem in an n-dimensional Euclidean space, n ≥q 2, containing finitely many obstacles with boundaries possessing a smooth structure. Obstacle boundaries are assumed to ...
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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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Extracting text from an image using a Visual Question Answering (VQA) system is an application at the intersection of computer vision and Natural Language Processing (NLP) to help blind people better view and comprehe...
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Distance and size estimation of objects of interests is an inevitable task for many navigation and obstacle avoidance algorithms mainly used in autonomus and robotic systems. Stereo vision systems, inspired by human v...
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