Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Study of neural network parameters in detecting heart disease
The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.
Read More...Feature extraction from peak detection algorithms for enhanced EMG-based hand gesture recognition models
This manuscript evaluates peak detection algorithms for feature extraction in EMG-based hand gesture recognition using a random forest classifier. The study demonstrates that wavelet-based peak detection features achieve the highest classification accuracy (96.5%), outperforming other methods. The results highlight the potential of peak features to improve EMG-based prosthetic control systems.
Read More...Analyzing carbon dividends’ impact on financial security via ML & metaheuristic search
Impact of carbon tax and dividend on financial security
Read More...Predicting the factors involved in orthopedic patient hospital stay
Long hospital stays can be stressful for the patient for many reasons. We hypothesized that age would be the greatest predictor of hospital stay among patients who underwent orthopedic surgery. Through our models, we found that severity of illness was indeed the highest factor that contributed to determining patient length of stay. The other two factors that followed were the facility that the patient was staying in and the type of procedure that they underwent.
Read More...Entropy-based subset selection principal component analysis for diabetes risk factor identification
In this article, the authors looked at developing a strategy that would allow for earlier diagnosis of Diabetes as that improves long-term outcomes. They were able to find that BMI, tricep skin fold thickness, and blood pressure are the risk factors with the highest accuracy in predicting diabetes risk.
Read More...Evaluating TensorFlow image classification in classifying proton collision images for particle colliders
In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.
Read More...Analysis of professional and amateur tennis serves using computer pose detection
The authors looked at the dynamics of tennis serves from professional and amateur athletes.
Read More...Impact of contamination variability on convolutional neural network accuracy in recycling classification
The authors looked at the ability of a convolutional neural network (CNN) to sort contaminated recycling, with varying levels of contamination. They found as contamination levels increased, the CNN faced more difficulty correctly classifying items.
Read More...Towards multimodal longitudinal analysis for predicting cognitive decline
Understanding and predicting cognitive decline in Alzheimer's disease
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