Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
1 School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India 2 Centre for Smart Grid Technologies, Vellore Institute of Technology, Chennai, Tamil Nadu, ...
In order to explore the medication rules of Shang Han Lun, this article conducted complex network analysis and cluster analysis on the 112 prescriptions in Shang Han Lun. Statistical and network ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
In today's digital age, the convergence of science education and machine learning technologies has the potential to revolutionize the teaching and learning processes. This research, conducted by a ...
The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...
A machine learning algorithm used gene expression profiles of patients with gout to predict flares. The PyTorch neural network performed best, with an area under the curve of 65%. The PyTorch model ...
Abstract: What if machine learning could predict inverter harmonics before prototyping? Conventional pulse width modulation (PWM) techniques in cascaded H-bridge (CHB) multilevel inverters (MLIs) ...
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