IEEE

Integrating Advanced Techniques: RFE-SVM Feature Engineering and Nelder-Mead Optimized XGBoost for Accurate Lung Cancer Prediction

Abstract: Early detection of lung cancer is crucial for improving patient survival and reducing mortality. However, medical datasets often face challenges like irrelevant features and class imbalance, ...

New Study Reveals Powerful New Method Can Distinguish Schizophrenia from Healthy Using Brain SPECT Imaging

Reports demonstrates that whole-brain Single Photon Emission Computed Tomography (SPECT) imaging, combined with advanced ...
News-Medical.Net

AI model identifies where snoring starts in the airway

A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.
Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
HealthDay on MSN

Unique protein signature IDs pediatric-onset inflammatory bowel disease

A unique protein signature has been identified for pediatric-onset inflammatory bowel disease (IBD), which is associated with ...
IEEE

Learning the Optimal Discriminant SVM With Feature Extraction

Abstract: Subspace learning and Support Vector Machine (SVM) are two critical techniques in pattern recognition, playing pivotal roles in feature extraction and classification. However, how to learn ...