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Development and Validation of a Machine Learning Algorithm After Primary Total Hip Arthroplasty: Applications to Length of Stay and Payment Models.

The Journal of arthroplasty
BACKGROUND: Value-based payment programs in orthopedics, specifically primary total hip arthroplasty (THA), present opportunities to apply forecasting machine learning techniques to adjust payment models to a specific patient or population. The objec...

Social robots to support children's well-being under medical treatment: A systematic state-of-the-art review.

Journal of child health care : for professionals working with children in the hospital and community
Hospitalization is a stressful experience for children. Socially assistive robots (SARs), designed to interact with humans, might be a means to mitigate a child's stress and support its well-being. A systematic state-of-the-art review was performed t...

Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach.

Journal of biomedical informatics
INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a serious problem. This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.

Machine Learning and Primary Total Knee Arthroplasty: Patient Forecasting for a Patient-Specific Payment Model.

The Journal of arthroplasty
BACKGROUND: Value-based and patient-specific care represent 2 critical areas of focus that have yet to be fully reconciled by today's bundled care model. Using a predictive naïve Bayesian model, the objectives of this study were (1) to develop a mach...

Risk prediction using natural language processing of electronic mental health records in an inpatient forensic psychiatry setting.

Journal of biomedical informatics
OBJECTIVE: Instruments rating risk of harm to self and others are widely used in inpatient forensic psychiatry settings. A potential alternate or supplementary means of risk prediction is from the automated analysis of case notes in Electronic Health...

Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
BACKGROUND: The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatmen...

An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest.

Journal of the American Heart Association
BACKGROUND: In-hospital cardiac arrest is a major burden to public health, which affects patient safety. Although traditional track-and-trigger systems are used to predict cardiac arrest early, they have limitations, with low sensitivity and high fal...

Time series model for forecasting the number of new admission inpatients.

BMC medical informatics and decision making
BACKGROUND: Hospital crowding is a rising problem, effective predicting and detecting managment can helpful to reduce crowding. Our team has successfully proposed a hybrid model combining both the autoregressive integrated moving average (ARIMA) and ...

Feasibility and efficacy of a robotic device for hand rehabilitation in hemiplegic stroke patients: a randomized pilot controlled study.

Clinical rehabilitation
OBJECTIVE: The purpose of the study was to evaluate the feasibility and efficacy of robot-assisted hand rehabilitation in improving arm function abilities in sub-acute hemiplegic patients.