AJR. American journal of roentgenology
Feb 1, 2019
OBJECTIVE: The purpose of this article is to compare traditional versus machine learning-based computer-aided detection (CAD) platforms in breast imaging with a focus on mammography, to underscore limitations of traditional CAD, and to highlight pote...
PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, these predictive models have several limitations, such as user convenience and reproducibility. The purpose of this study was to develop a T2DM predic...
PURPOSE: The aim of this study was to assess the potential of machine learning with multiparametric magnetic resonance imaging (mpMRI) for the early prediction of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) and of survival ...
PURPOSE: To evaluate a deep learning-based method to automatically detect graft detachment (GD) after Descemet membrane endothelial keratoplasty (DMEK) in anterior segment optical coherence tomography (AS-OCT).
Breast cancer is a leading cause of cancer death among women in the USA. Screening mammography is effective in reducing mortality, but has a high rate of unnecessary recalls and biopsies. While deep learning can be applied to mammography, large-scale...
The aim of this study is to develop a fully automated convolutional neural network (CNN) method for quantification of breast MRI fibroglandular tissue (FGT) and background parenchymal enhancement (BPE). An institutional review board-approved retrospe...
BACKGROUND AND OBJECTIVES: Recent years have seen social robotic pets introduced as a means of treating behavioral and psychological symptoms of dementia, and many show promising potential. In this study, we sought to explore family members' percepti...
Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
Jan 4, 2019
INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological moment...
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