AIMC Topic: Electronic Health Records
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Comparing neural language models for medical concept representation and patient trajectory prediction.
Artificial intelligence in medicine
Mar 10, 2025
Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise in automatically deriving medical concept representations from clinical data. However, the comparat...
Using Natural Language Processing in the LACE Index Scoring Tool to Predict Unplanned Trauma and Surgical Readmissions in South Africa.
World journal of surgery
Mar 9, 2025
BACKGROUND: Unplanned and potentially avoidable readmission within 30 days post discharge is a major financial burden.
AI-Driven decision-making for personalized elderly care: a fuzzy MCDM-based framework for enhancing treatment recommendations.
BMC medical informatics and decision making
Mar 8, 2025
BACKGROUND: Global healthcare systems face enormous challenges due to the ageing population, demanding novel measures to assure long-term efficacy and viability. The expanding senior population, which requires specialised and efficient healthcare sol...
NLP modeling recommendations for restricted data availability in clinical settings.
BMC medical informatics and decision making
Mar 7, 2025
BACKGROUND: Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising solution, but its application in cl...
Applying Robotic Process Automation to Monitor Business Processes in Hospital Information Systems: Mixed Method Approach.
JMIR medical informatics
Mar 7, 2025
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...
Advanced NLP-driven predictive modeling for tailored treatment strategies in gastrointestinal cancer.
SLAS technology
Mar 6, 2025
Gastrointestinal cancer represents a significant health burden, necessitating innovative approaches for personalized treatment. This study aims to develop an advanced natural language processing (NLP)-driven predictive modeling framework for tailored...
Development of a natural language processing algorithm to extract social determinants of health from clinician notes.
American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
Mar 6, 2025
Disparities in access to the organ transplant waitlist are well-documented, but research into modifiable factors has been limited due to a lack of access to organized prewaitlisting data. This study aimed to develop a natural language processing (NLP...
Development and Validation of an Electronic Health Record-Based, Pediatric Acute Respiratory Distress Syndrome Subphenotype Classifier Model.
Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
Mar 6, 2025
OBJECTIVE: To determine if hyperinflammatory and hypoinflammatory pediatric acute respiratory distress syndrome (PARDS) subphenotypes defined using serum biomarkers can be determined solely from electronic health record (EHR) data using machine learn...
Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study.
Journal of medical Internet research
Mar 6, 2025
BACKGROUND: Data on the social determinants of health could be used to improve care, support quality improvement initiatives, and track progress toward health equity. However, this data collection is not widespread. Artificial intelligence (AI), spec...
Preprocessing of natural language process variables using a data-driven method improves the association with suicide risk in a large veterans affairs population.
Computers in biology and medicine
Mar 5, 2025
OBJECTIVE: Suicide risk assessment has historically relied heavily on clinical evaluations and patient self-reports. Natural language processing (NLP) of electronic health records (EHRs) provides an alternative approach for extracting risk predictors...
United States Department of Defense
Suicide, Completed
Predictive Learning Models
Psychological Well-Being
Natural Language Processing
United States Department of Veterans Affairs
Veterans
Male
Middle Aged
Risk Assessment
Suicide Prevention
United States
Case-Control Studies
Adolescent
Aged, 80 and over
Young Adult
Adult
Electronic Health Records
Humans
Female
Aged
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