AI Medical Compendium Journal:
JMIR medical informatics

Showing 21 to 30 of 65 articles

Improving Systematic Review Updates With Natural Language Processing Through Abstract Component Classification and Selection: Algorithm Development and Validation.

JMIR medical informatics
BACKGROUND: A challenge in updating systematic reviews is the workload in screening the articles. Many screening models using natural language processing technology have been implemented to scrutinize articles based on titles and abstracts. While the...

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study.

JMIR medical informatics
BACKGROUND: Machine learning (ML) systems in health care have the potential to enhance decision-making but often fail to address critical issues such as prediction explainability, confidence, and robustness in a context-based and easily interpretable...

Convolutional Neural Network Models for Visual Classification of Pressure Ulcer Stages: Cross-Sectional Study.

JMIR medical informatics
BACKGROUND: Pressure injuries (PIs) pose a negative health impact and a substantial economic burden on patients and society. Accurate staging is crucial for treating PIs. Owing to the diversity in the clinical manifestations of PIs and the lack of ob...

Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.

JMIR medical informatics
BACKGROUND: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. ...

The Perceptions of Potential Prerequisites for Artificial Intelligence in Danish General Practice: Vignette-Based Interview Study Among General Practitioners.

JMIR medical informatics
BACKGROUND: Artificial intelligence (AI) has been deemed revolutionary in medicine; however, no AI tools have been implemented or validated in Danish general practice. General practice in Denmark has an excellent digitization system for developing an...

Applying Robotic Process Automation to Monitor Business Processes in Hospital Information Systems: Mixed Method Approach.

JMIR medical informatics
BACKGROUND: Electronic medical records (EMRs) have undergone significant changes due to advancements in technology, including artificial intelligence, the Internet of Things, and cloud services. The increasing complexity within health care systems ne...

The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review.

JMIR medical informatics
BACKGROUND: Artificial intelligence (AI) has shown exponential growth and advancements, revolutionizing various fields, including health care. However, domain adaptation remains a significant challenge, as machine learning (ML) models often need to b...

Predicting Readmission Among High-Risk Discharged Patients Using a Machine Learning Model With Nursing Data: Retrospective Study.

JMIR medical informatics
BACKGROUND: Unplanned readmissions increase unnecessary health care costs and reduce the quality of care. It is essential to plan the discharge care from the beginning of hospitalization to reduce the risk of readmission. Machine learning-based readm...

Performance Improvement of a Natural Language Processing Tool for Extracting Patient Narratives Related to Medical States From Japanese Pharmaceutical Care Records by Increasing the Amount of Training Data: Natural Language Processing Analysis and Validation Study.

JMIR medical informatics
BACKGROUND: Patients' oral expressions serve as valuable sources of clinical information to improve pharmacotherapy. Natural language processing (NLP) is a useful approach for analyzing unstructured text data, such as patient narratives. However, few...

Predicting Agitation-Sedation Levels in Intensive Care Unit Patients: Development of an Ensemble Model.

JMIR medical informatics
BACKGROUND: Agitation and sedation management is critical in intensive care as it affects patient safety. Traditional nursing assessments suffer from low frequency and subjectivity. Automating these assessments can boost intensive care unit (ICU) eff...