AIMC Topic: Wounds and Injuries
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Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.
Surgery
Mar 23, 2025
BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic regression in forecasting discharge against medical advice occurrences needs to be evaluated.
Complex wound analysis using AI.
Computers in biology and medicine
Mar 18, 2025
Impaired wound healing is a significant clinical challenge. Standard wound analysis approaches are macroscopic, with limited histological assessments that rely on visual inspection of haematoxylin and eosin (H&E)-stained sections of biopsies. The ana...
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.
Utilization of non-invasive ventilation before prehospital emergency anesthesia in trauma - a cohort analysis with machine learning.
Scandinavian journal of trauma, resuscitation and emergency medicine
Mar 3, 2025
BACKGROUND: For preoxygenation, German guidelines consider non-invasive ventilation (NIV) as a possible method in prehospital trauma care in the absence of aspiration, severe head or face injuries, unconsciousness, or patient non-compliance. As data ...
Artificial Intelligence Methods for Diagnostic and Decision-Making Assistance in Chronic Wounds: A Systematic Review.
Journal of medical systems
Feb 19, 2025
Chronic wounds, which take over four weeks to heal, are a major global health issue linked to conditions such as diabetes, venous insufficiency, arterial diseases, and pressure ulcers. These wounds cause pain, reduce quality of life, and impose signi...
Injury degree appraisal of large language model based on retrieval-augmented generation and deep learning.
International journal of law and psychiatry
Feb 18, 2025
Large Language Models (LLMs) have shown impressive performance in various natural language processing tasks. However, their application in specialized domains like forensic injury appraisal remains challenging due to the lack of domain-specific knowl...
Retrieval-augmented generation improves precision and trust of a GPT-4 model for emergency radiology diagnosis and classification: a proof-of-concept study.
European radiology
Feb 14, 2025
OBJECTIVES: This study evaluated the effect of enhancing a GPT-4 model with retrieval-augmented generation on its ability to diagnose and classify traumatic injuries based on radiology reports.
A comparative analysis of trauma-related mortality in South Korea using classification models.
International journal of medical informatics
Feb 1, 2025
BACKGROUND: Reducing mortality among severe trauma patients requires the establishment of an effective emergency transportation system and the rapid transfer of patients to appropriate medical facilities. Machine learning offers significant potential...
Enhancing trauma triage in low-resource settings using machine learning: a performance comparison with the Kampala Trauma Score.
BMC emergency medicine
Jan 23, 2025
BACKGROUND: Traumatic injuries are a leading cause of morbidity and mortality globally, with a disproportionate impact on populations in low- and middle-income countries (LMICs). The Kampala Trauma Score (KTS) is frequently used for triage in these s...
Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study.
Journal of medical Internet research
Jan 22, 2025
BACKGROUND: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic morta...
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