INTRODUCTION: In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.
Computer methods and programs in biomedicine
Jan 9, 2020
BACKGROUND AND OBJECTIVE: The interrupted time-series (ITS) concept is performed using linear regression to evaluate the impact of policy changes in public health at a specific time. Objectives of this study were to verify, with an artificial intelli...
Computer methods and programs in biomedicine
Dec 23, 2019
BACKGROUND AND OBJECTIVE: Malposition of the acetabular component causes dislocation and prosthetic impingement after Total Hip Arthroplasty (THA), which significantly affects the postoperative quality of life and implant longevity. The position of t...
Expert review of pharmacoeconomics & outcomes research
Sep 13, 2019
: Metamodels have been used to approximate complex simulations and have many applications with sensitivity analysis, optimization, etc. However, their use in health economics is very limited. Application of artificial neural network (ANN) with a heal...
We propose a method for automatic segmentation of individual muscles from a clinical CT. The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to th...
BACKGROUND: Quality monitoring is increasingly important to support and assure sustainability of the orthopedic practice. Surgeons in nonacademic settings often lack resources to accurately monitor quality of care. Widespread use of electronic medica...
BACKGROUND: Tracking patient-generated health data (PGHD) following total joint arthroplasty (TJA) may enable data-driven early intervention to improve clinical results. We aim to demonstrate the feasibility of combining machine learning (ML) with PG...
BACKGROUND: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for predicting this adverse outcome. The purpose of this study is to develop machine learning algorithms...
BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poised to expand orthopedic surgery frontiers. Lower extremity arthroplasty is uniquely positioned to mos...
BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarchical layers to build models, offering the ability to advance value-based healthcare by better predicting patient outcomes and costs of a given treatm...