AIMC Topic: Research Design

Clear Filters Showing 481 to 490 of 646 articles

From protocolized to person-centered chronic care in general practice: study protocol of an action-based research project (COPILOT).

Primary health care research & development
AIM: To develop a proactive person-centered care approach for persons with (multiple) chronic diseases in general practice, and to explore the impact on 'Quadruple aims': experiences of patients and professionals, patient outcomes and costs of resour...

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol.

BMC psychiatry
BACKGROUND: The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies to collect data and extract relevant information's for patient management. Artificial intelligence (AI) techniques allow processing o...

Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.

International journal of medical informatics
INTRODUCTION: Previous biomedical studies identified many lifestyle exposures that could possibly represent risk factors for dementia in general or dementia due to Alzheimer's disease (AD). These lifestyle exposures are mainly mentioned in free-text ...

Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.

Research synthesis methods
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free s...

Iterative processes: a review of semi-supervised machine learning in rehabilitation science.

Disability and rehabilitation. Assistive technology
To define semi-supervised machine learning (SSML) and explore current and potential applications of this analytic strategy in rehabilitation research. We conducted a scoping review using PubMed, GoogleScholar and Medline. Studies were included if th...

Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.

Journal of the American College of Radiology : JACR
OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for patient safety. The definitive communication is the radiology free-text report. Quality assurance in...

A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop.

Journal of the American College of Radiology : JACR
Advances in machine learning in medical imaging are occurring at a rapid pace in research laboratories both at academic institutions and in industry. Important artificial intelligence (AI) tools for diagnostic imaging include algorithms for disease d...

Effects of Assistive Robot Behavior on Impressions of Patient Psychological Attributes: Vignette-Based Human-Robot Interaction Study.

Journal of medical Internet research
BACKGROUND: As robots are increasingly designed for health management applications, it is critical to not only consider the effects robots will have on patients but also consider a patient's wider social network, including the patient's caregivers an...

Machine learning for prediction of sudden cardiac death in heart failure patients with low left ventricular ejection fraction: study protocol for a retroprospective multicentre registry in China.

BMJ open
INTRODUCTION: Left ventricular ejection fraction (LVEF) ≤35%, as current significant implantable cardioverter-defibrillator (ICD) indication for primary prevention of sudden cardiac death (SCD) in heart failure (HF) patients, has been widely recognis...

Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural network (DCNN) model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with cystic fibrosis (CF), performing similar...