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Found 5 papers, 3 papers with code
Predictive Model Development to Identify Failed Healing in Patients after Non-Union Fracture Surgery
To demonstrate the effectiveness of ML in identifying candidates at risk of failed non-union healing, we applied three ML models (logistic regression, support vector machine, and XGBoost) to the clinical dataset TRUFFLE, which includes 797 patients with long bone non-union.
Time Series Classification for Detecting Parkinson's Disease from Wrist Motions
We used a random search to find the highest-scoring InceptionTime architecture and compared it to ROCKET with a ridge classifier and a multi-layer perceptron (MLP) on wrist motions of PD patients.
A Multi-layer Gaussian Process for Motor Symptom Estimation in People with Parkinson's Disease
The assessment of Parkinson's disease (PD) poses a significant challenge as it is influenced by various factors which lead to a complex and fluctuating symptom manifestation.
Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and Visualization
Parkinson's Disease (PD) is characterized by disorders in motor function such as freezing of gait, rest tremor, rigidity, and slowed and hyposcaled movements.
Data Augmentation of Wearable Sensor Data for Parkinson's Disease Monitoring using Convolutional Neural Networks
While convolutional neural networks (CNNs) have been successfully applied to many challenging classification applications, they typically require large datasets for training.
