Investigating the challenges and generalizability of deep learning brain conductivity mapping.
Sign Up to like & getrecommendations! Published in 2020 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/ab9356
Abstract: PURPOSE To investigate deep learning electrical properties tomography (EPT) for application on different simulated and in-vivo datasets including pathologies for brain conductivity reconstructions. METHODS 3D patch-based convolutional neural networks were trained to predict conductivity maps… read more here.
Keywords: conductivity labels; deep learning; conductivity; brain conductivity ... See more keywords
AI-powered prediction of critical properties and boiling points: a hybrid ensemble learning and QSPR approach
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-025-01062-9
Abstract: In this paper, we propose a robust deep-learning model based on a Quantitative Structure − Property Relationship (QSPR) approach for estimating the critical temperature (TC), critical pressure (PC), acentric factor (ACEN) and normal boiling point (NBP) of… read more here.
Keywords: qspr approach; networks trained; prediction; neural networks ... See more keywords