Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)–based models may be the solution ...

Azillah Binti Othman, IAEA Department of Nuclear Sciences and Applications Ayhan Evrensel, IAEA Department of Nuclear Sciences and Applications The IAEA is inviting research organizations to join a ...

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Abstract: Amyotrophic Lateral Sclerosis (ALS) is a critical disease, and many people suffer from it. Different diagnostic models have been proposed for ALS detection. However, these models still have ...

(a) The arrows in the figure show the procedure for extracting the damage index, (b) The result shows the detection result of the damage index. A research team from Jinan University, Dongguan ...

This project evaluates how effectively static features extracted from Windows Portable Executable (PE) files can distinguish ransomware from benign software using supervised machine learning. This ...

Today, the plastics industry stands at the threshold of a technological revolution, with artificial intelligence and machine learning poised to transform everything from material development to ...

Abstract: Recently, the rapid expansion of the Internet of Things (IoT) has opened up new possibilities and introduced significant security challenges. This evolution enhances everyday life but also ...