Frontiers

Machine learning-based detection of cognitive decline using SSWTRT: classification performance and decision analysis

Introduction: Early detection of cognitive decline is essential for preventing dementia progression, yet conventional screening tools such as the Mini-Mental State Examination (MMSE) require trained ...
IEEE

Automated Shape Classification Using SAR Imaging and Machine Learning

Abstract: The proposed method involves generating milli-meter Wave Frequency Modulated Continuous Wave (mmWave FMCW) radar image data through MATLAB modeling, reconstructing images using SAR imaging ...
IEEE

Deep Active Learning for Image Hierarchical Classification by Introducing Dependencies and Constraints Between Classes

Abstract: Deep active learning (DeepAL) extends supervised deep learning to human-machine interactive scenarios with limited annotation budgets. Most existing DeepAL approaches for visual recognition ...
National Academies of Sciences%2c Engineering%2c and Medicine

Making Machine Learning Safer in High-Stakes Settings

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...
C&EN

CO 2 Isotopologue Quantification Using Direct Frequency Comb Spectroscopy and Machine Learning

Australian Institute for Machine Learning (AIML), School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia Institute for Photonics and Advanced ...
C&EN

Improving Machine Learning Classification Predictions through SHAP and Features Analysis Interpretation

Department of Life Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi 103, 41125 Modena, Italy Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, ...