Advanced ECG feature extraction and SVM classification for predicting defibrillation success in OHCA
Out-of-hospital cardiac arrest (OHCA) represents a critical challenge for emergency medical services, with the necessity for rapid and accurate prediction of defibrillation outcomes to enhance patient ...
Learn how to classify sleep stages using EEG data with Python, MNE, and Scikit-learn in this step-by-step guide. House GOP fails to pass tax and spending bill after key committee vote Game of Thrones: ...
Hands-on coding of a multiclass neural network from scratch, with softmax and one-hot encoding. #Softmax #MulticlassClassification #PythonAI The 2 House Republicans who voted no on Trump's sweeping ...
Works Well for Clear Margin of Separation If the two classes (Malignant vs Benign) are well-separated, SVM performs strongly by maximizing the margin between them. Robust to Overfitting (with Proper ...
Abstract: The manual diagnosis of diabetic retinopathy (DR) is often invasive, time-consuming, expensive, and prone to human error. Additionally, it can be subjective ...
This study introduces the XGBoost Multimodal Autism Predictor (XMAP), an interpretable machine learning framework designed to improve ASD classification by integrating publicly available behavioral ...
Abstract: For three-dimensional (3D) cultural heritage objects paintings that are destroyed or dented and can no longer be 3D scanned to establish digital archives, this study suggests a deep learning ...
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