Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.

This project is a full machine learning pipeline for Star/Galaxy classification using the SDSS dataset. It also contains a detailed report on the development and a DockerFile to easily replicate the ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

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 = ...

1 Department of Nuclear Medicine, Yancheng No. 1 Peoples’ Hospital, Yancheng, China 2 Department of Hematology, Yancheng No. 1 Peoples’ Hospital, Yancheng, China Objective: Accurate differentiation ...

1 Information Statistics Center, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China 2 School of Computer Science and Technology, Hubei Business ...

Today, Apple published on its Machine Learning Research blog, select recordings from its 2024 Workshop on Human-Centered Machine Learning (HCML), highlighting its work on responsible AI development.

Abstract: In this paper, we propose a learning-based method utilizing the Soft Actor-Critic (SAC) algorithm to train a binary Support Vector Machine (SVM) classifier. This classifier is designed to ...

Apple’s MLX machine learning framework, originally designed for Apple Silicon, is getting a CUDA backend, which is a pretty big deal. Here’s why. The work is being led by developer @zcbenz on GitHub ...