AIMC Topic: Outcome Assessment, Health Care

Clear Filters Showing 31 to 40 of 213 articles

Outcome measures applied to robotic assistive technology for people with cerebral palsy: a pilot study.

Disability and rehabilitation. Assistive technology
The application of robotic devices is being used as Assistive Technology (AT) for improving rehabilitation interventions. The purposes of this research were to (1) test a novel low-cost robotic AT to support interventions for people with Cerebral Pal...

The Promise and Challenges of Practice-Oriented Research: A Commentary on the Special Issue.

Administration and policy in mental health
At the centre of POR is the concept of collaboration between patients, therapists, agencies, and third-party payers. For this commentary, I review the articles of the special issue with attention to both the opportunities and challenges offered by pr...

Training intensity of robot-assisted gait training in children with cerebral palsy.

Developmental medicine and child neurology
AIM: We compared three different intensities of robot-assisted gait training (RAGT) for achieving favourable outcomes in children with cerebral palsy (CP).

Seeing the whole elephant: integrated advanced data analytics in support of RWE for the development and use of innovative pharmaceuticals.

Expert review of pharmacoeconomics & outcomes research
INTRODUCTION: The 21 century has brought about significant technological advancement, allowing the collection of new types of data from the real world on an unprecedented scale. The healthcare industry will benefit immensely from this abundance of pa...

Leveraging Data and Technology to Enhance Interdisciplinary Collaboration and Health Outcomes.

Yearbook of medical informatics
OBJECTIVE: To give an overview of recent research and propose a selection of best papers published in 2022 in Informatics for One Health.

Predicting treatment response using machine learning: A registered report.

The British journal of clinical psychology
OBJECTIVE: Previous research on psychotherapy treatment response has mainly focused on outpatients or clinical trial data which may have low ecological validity regarding naturalistic inpatient samples. To reduce treatment failures by proactively scr...

Predicting Outcomes of Antidepressant Treatment in Community Practice Settings.

Psychiatric services (Washington, D.C.)
OBJECTIVE: The authors examined whether machine-learning models could be used to analyze data from electronic health records (EHRs) to predict patients' responses to antidepressant medications.

Use of mobile technology to identify behavioral mechanisms linked to mental health outcomes in Kenya: protocol for development and validation of a predictive model.

BMC research notes
OBJECTIVE: This study proposes to identify and validate weighted sensor stream signatures that predict near-term risk of a major depressive episode and future mood among healthcare workers in Kenya.

Individual-Level Prediction of Exposure Therapy Outcome Using Structural and Functional MRI Data in Spider Phobia: A Machine-Learning Study.

Depression and anxiety
Machine-learning prediction studies have shown potential to inform treatment stratification, but recent efforts to predict psychotherapy outcomes with clinical routine data have only resulted in moderate prediction accuracies. Neuroimaging data showe...