Frontiers

A clinical prediction model for schizophrenia based on machine learning algorithms

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...
Frontiers

Liberating the open and distance learning model from the chains of oppressive education theories

This study argues that open and distance learning (ODL) continues to function as a platform for producing factory-like workers and white-collar laborers whose primary function is to serve the ...
IEEE

Reinforcement Learning With Model Predictive Control for Highway Ramp Metering

Abstract: In the backdrop of an increasingly pressing need for effective urban and highway transportation systems, this work explores the synergy between model-based and learning-based strategies to ...
IEEE

Digital In-Memory Compute for Machine Learning Applications With Input and Model Security

Abstract: Digital in-memory compute (IMC) architectures allow for a balance of the high accuracy and precision necessary for many machine learning applications, with high data reuse and parallelism to ...
Journal of Medical Internet Research

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

We evaluated machine learning algorithms (random forest [RF], extra-trees classifier, and light gradient boosting machine) and selected the RF model as the final model based on its performance. To ...