AIMC Topic: Reproducibility of Results

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Ultra-low-dose chest CT imaging of COVID-19 patients using a deep residual neural network.

European radiology
OBJECTIVES: The current study aimed to design an ultra-low-dose CT examination protocol using a deep learning approach suitable for clinical diagnosis of COVID-19 patients.

Kinematic Calibration of a Parallel 2-UPS/RRR Ankle Rehabilitation Robot.

Journal of healthcare engineering
In order to better perform rehabilitation training on the ankle joint complex in the direction of dorsiflexion/plantarflexion and inversion/eversion, especially when performing the isokinetic muscle strength exercise, we need to calibrate the kinemat...

Deep learning-based lumbosacral reconstruction for difficulty prediction of percutaneous endoscopic transforaminal discectomy at L5/S1 level: A retrospective cohort study.

International journal of surgery (London, England)
BACKGROUND: Deep learning has been validated as a promising technique for automatic segmentation and rapid three-dimensional (3D) reconstruction of lumbosacral structures on CT. Simulated foraminoplasty of percutaneous endoscopic transforaminal disce...

Neural Network-Based Study about Correlation Model between TCM Constitution and Physical Examination Indexes Based on 950 Physical Examinees.

Journal of healthcare engineering
PURPOSE: To establish the correlation model between Traditional Chinese Medicine (TCM) constitution and physical examination indexes by backpropagation neural network (BPNN) technology. A new method for the identification of TCM constitution in clini...

Fault Diagnosis for High-Speed Train Axle-Box Bearing Using Simplified Shallow Information Fusion Convolutional Neural Network.

Sensors (Basel, Switzerland)
Axle-box bearings are one of the most critical mechanical components of the high-speed train. Vibration signals collected from axle-box bearings are usually nonlinear and nonstationary, caused by the complicated operating conditions. Due to the high ...

A Smart Service Platform for Cost Efficient Cardiac Health Monitoring.

International journal of environmental research and public health
AIM: In this study we have investigated the problem of cost effective wireless heart health monitoring from a service design perspective.

Fully-Connected Neural Networks with Reduced Parameterization for Predicting Histological Types of Lung Cancer from Somatic Mutations.

Biomolecules
Several challenges appear in the application of deep learning to genomic data. First, the dimensionality of input can be orders of magnitude greater than the number of samples, forcing the model to be prone to overfitting the training dataset. Second...