To assess whether application of a support vector machine learning algorithm to ancillary data obtained from posterior-anterior dual-energy X-ray absorptiometry (DEXA) studies could identify patients with lumbar spine (L1-L4) vertebral body fractures...
Journal of pediatric endocrinology & metabolism : JPEM
Jan 28, 2020
Background Growth hormone (GH) treatment has become a common practice in Turner syndrome (TS). However, there are only a few studies on the response to GH treatment in TS. The aim of this study is to predict the responsiveness to GH treatment and to ...
AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and t...
Despite the high level of interest in the use of machine learning (ML) and neuroimaging to detect psychosis at the individual level, the reliability of the findings is unclear due to potential methodological issues that may have inflated the existing...
American journal of clinical pathology
Jan 2, 2020
OBJECTIVES: Peripheral blood flow cytometry (PBFC) is useful for evaluating circulating hematologic malignancies (HM) but has limited diagnostic value for screening. We used machine learning to evaluate whether clinical history and CBC/differential p...
Canadian journal of surgery. Journal canadien de chirurgie
Jan 1, 2020
The cancellation of large numbers of surgical procedures because of the coronavirus disease 2019 (COVID-19) pandemic has drastically extended wait lists and negatively affected patient care and experience. As many facilities resume clinical work owin...
INTRODUCTION: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one su...
BACKGROUND: Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess...
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