Medicare

Evaluating the performance of a predictive modeling approach to identifying members at high-risk of hospitalization.

To evaluate the risk-of-hospitalization (ROH) models developed at Blue Cross Blue Shield of Louisiana (BCBSLA) and compare this approach to the DxCG risk-score algorithms utilized by many health plans. Time zero for this study was December 31, 2016. BCBSLA members were eligible for study inclusion if they were fully insured; aged 80 years or younger; and had continuous enrollment starting on or b...

Sentiment Analysis of the News Media on Artificial Intelligence Does Not Support Claims of Negative Bias Against Artificial Intelligence.

Artificial intelligence (AI) is a hot topic in digital health, as automated systems are being adopted throughout the health care system. Because they are still flexible, emerging technologies can be shaped significantly by media representations as well as public engagement with science. In this context, we examine the belief that negative news media coverage of AI-and specifically, the alleged use...

Development and validation of 15-month mortality prediction models: a retrospective observational comparison of machine-learning techniques in a national sample of Medicare recipients.

OBJECTIVE: The objective is to develop and validate a predictive model for 15-month mortality using a random sample of community-dwelling Medicare ben...

A review of cable-driven rehabilitation devices.

To conduct a survey on the research and development of cable-driven rehabilitation devices (CDRDs). This review searches in the databases of PubMed,...

Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a...

Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.

An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and qua...

Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a commo...

Effect of verticalization with Erigo® in the acute rehabilitation of severe acquired brain injury.

The recovery of the orthostatism after a severe acquired brain injury (sABI) is an essential objective to pursue in order to avoid the occurrence of s...

Concept embedding to measure semantic relatedness for biomedical information ontologies.

There have been many attempts to identify relationships among concepts corresponding to terms from biomedical information ontologies such as the Unifi...

Estimating the Population Average Treatment Effect in Observational Studies with Choice-Based Sampling.

We consider causal inference in observational studies with choice-based sampling, in which subject enrollment is stratified on treatment choice. Choic...

Deep-learning augmented RNA-seq analysis of transcript splicing.

A major limitation of RNA sequencing (RNA-seq) analysis of alternative splicing is its reliance on high sequencing coverage. We report DARTS (https://...

A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis.

This study reviews the technique of convolutional neural network (CNN) applied in a specific field of mammographic breast cancer diagnosis (MBCD). It ...

A Novel Technique for Multi Biometric Cryptosystem Using Fuzzy Vault.

Biometric authentication is the process of recognizing a person by means of his\her psychological or behavioral traits. One of the most important issu...

Impact of nominal photon energies on normal tissue sparing in knowledge-based radiotherapy treatment planning for rectal cancer patients.

The interactive adjustment of the optimization objectives during the treatment planning process has made it difficult to evaluate the impact of beam q...

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions.

IMPORTANCE: Current approaches to identifying individuals at high risk for opioid overdose target many patients who are not truly at high risk.

Transfer learning for predicting human skin sensitizers.

Computational prioritization of chemicals for potential skin sensitization risks plays essential roles in the risk assessment of environmental chemica...

Applications of artificial neural networks in health care organizational decision-making: A scoping review.

Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduc...

Sleep Duration and Diabetic Kidney Disease.

Abnormally short or long durations of sleep have been proposed as a risk factors for diabetes and its micro- and macro-vascular complications. Howeve...

Prevalence of Vitamin D Inadequacy Among Chinese Postmenopausal Women: A Nationwide, Multicenter, Cross-Sectional Study.

We aimed to investigate the status of serum 25-hydroxyvitamin D [25(OH)D] among Chinese postmenopausal women in a multicenter cross-sectional study. ...

Case study: Evaluating quarter and composite milk sampling for detection of subclinical intramammary infections in dairy cattle.

Our objective was to evaluate a 200,000 cells/mL somatic cell count (SCC) cut-point on both the quarter and composite level to determine its effective...