IEEE

Two-Stage Self-Supervised Cycle-Consistency Transformer Network for Reducing Slice Gap in ...

Abstract: Magnetic resonance (MR) images are usually acquired with large slice gap in clinical practice, i.e., low resolution (LR) along the through-plane direction. It is feasible to reduce the slice ...
IEEE

Self-Supervised Multitask 3-D Partial Convolutional Neural Network for Random Noise ...

Abstract: Most existing traditional and deep learning (DL)-based methods used for random noise attenuation or reconstruction of seismic data typically only process 2-D data. Very few methods are able ...
BMJ

Clinical relevance of intracranial stenosis as false-positive findings of a deep learning ...

Objectives This study aims to explore the ability to identify high-grade intracranial arterial stenosis (ICAS) by an artificial intelligence (AI) designed to detect large vessel occlusions (LVO) and ...
GitHub

MoustafaSerag/applied-machine-learning-projects-scikit-learn

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
GitHub

PacktPublishing/Time-Series-Analysis-with-Python-Cookbook

Forecasting Using Supervised Machine Learning Chapter 12, Forecasting Using Supervised Machine Learning, will take you from classical time series forecasting techniques to more advanced machine ...