Major progress in disease genetics has been made through genome-wide association studies (GWASs). One of the key tasks for post-GWAS analyses is to identify causal noncoding variants with regulatory function. Here, on the basis of >2000 functional fe...
Gan to kagaku ryoho. Cancer & chemotherapy
Dec 1, 2019
BACKGROUND: Surgical site infections(SSIs)occur at a high frequency in patients after rectal cancer surgery and are readily aggravated. Therefore, prophylactic measures for infections based on the evaluation of the patient's perioperative risk are ve...
Journal of the American Medical Informatics Association : JAMIA
Dec 1, 2019
OBJECTIVE: The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.
The journals of gerontology. Series A, Biological sciences and medical sciences
Nov 13, 2019
BACKGROUND: Sleep characteristics related to duration, timing, continuity, and sleepiness are associated with mortality in older adults, but rarely considered in health recommendations. We applied machine learning to: (i) establish the predictive abi...
IMPORTANCE: Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperati...
The purpose of this study was to verify the usefulness of machine learning (ML) for selection of risk factors and development of predictive models for patients with sarcopenia.We collected medical records from Korean postmenopausal women based on Kor...
Studies in health technology and informatics
Aug 21, 2019
Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity...
OBJECTIVE: Surgical site infection (SSI) following a neurosurgical operation is a complication that impacts morbidity, mortality, and economics. Currently, machine learning (ML) algorithms are used for outcome prediction in various neurosurgical aspe...
OBJECTIVES: This study sought to develop and compare an array of machine learning methods to predict in-hospital mortality after transcatheter aortic valve replacement (TAVR) in the United States.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
This paper introduces a sparse embedding for electronic health record (EHR) data in order to predict hospital admission. We use a k-sparse autoencoder to embed the original registry data into a much lower dimension, with sparsity as a goal. Then, t-S...
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