Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Background: This study developed a machine learning model to predict postoperative heart failure (HF) risk in non-cardiac surgery patients. Methods: Using data from 489 patients (109 HF cases, 380 ...
A wave of pseudoscientific papers has tried to dismantle one of biology’s most fundamental truths: only two sexes exist, male and female. These papers often claim that sex is a broad “spectrum,” and ...
The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...
Cancer machine learning research is often limited by overparameterization and overfitting, which arise because cancer ‘omic’ variables significantly outnumber patient samples. Traditional feature ...
Abstract: Class imbalance occurs frequently in machine learning, particularly in binary classification tasks where the majority class has a significantly larger number of samples than the minority ...
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