Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

The risk of bias was evaluated using the Quality In Prognosis Studies tool and the Prediction model Risk Of Bias Assessment Tool by 2 investigators (MMS and MAS) independently. A narrative synthesis ...

Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as the Framingham ...

Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...

Steal a Brainrot Fuse Machine lets players combine up to four Brainrots for new, rare ones. There are two new secret Brainrots and several fusion combos with unique odds. Players can speed up fusions ...

Dusty plasma, a mixture of ions, electrons, and charged dust particles, is common throughout the universe. Understanding and modeling dusty plasma require precise knowledge of the complex interactions ...

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...

Diabetic peripheral neuropathy (DPN) is a common and debilitating complication of type 2 diabetes mellitus (T2DM), significantly impacting patients’ quality of life and increasing healthcare burdens.

Significant predictors were selected on the training set using recursive feature elimination methods, followed by prediction model development using 7 machine learning algorithms (logistic regression, ...

Abstract: Crop diseases have a disproportionately large economic effect on farmers and threaten food security. Predictive Model for Crop Disease and Management System, which uses machine and deep ...