The Journal of antimicrobial chemotherapy
Apr 1, 2019
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...
European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP)
Mar 1, 2019
The objective of this study was to determine whether the pretreatment human papillomavirus (HPV) genotype might predict the risk of cervical dysplasia persistence/recurrence. Retrospective analysis of prospectively collected data of consecutive 5104 ...
Investigative ophthalmology & visual science
Feb 1, 2019
PURPOSE: To develop and assess a method for predicting the likelihood of converting from early/intermediate to advanced wet age-related macular degeneration (AMD) using optical coherence tomography (OCT) imaging and methods of deep learning.
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...
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...
Karakurt N, Uslu İ, Aygün C, Albayrak C. Hematological disturbances in Down syndrome: single centre experience of thirteen years and review of the literature. Turk J Pediatr 2019; 61: 664-670. Neonates with Down syndrome (DS) may have hematological a...
To evaluate the value of the computer-aided diagnosis (CAD) program applied to diagnostic breast ultrasonography (US) based on operator experience.US images of 100 breast masses from 91 women over 2 months (from May to June 2015) were collected and r...
IMPORTANCE: Convolutional neural networks (CNNs) achieve expert-level accuracy in the diagnosis of pigmented melanocytic lesions. However, the most common types of skin cancer are nonpigmented and nonmelanocytic, and are more difficult to diagnose.