AIMC Topic: Registries
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Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke.
BMC neurology
May 7, 2024
BACKGROUND: Posterior Circulation Syndrome (PCS) presents a diagnostic challenge characterized by its variable and nonspecific symptoms. Timely and accurate diagnosis is crucial for improving patient outcomes. This study aims to enhance the early dia...
Development of a Predictive Model for Survival Over Time in Patients With Out-of-Hospital Cardiac Arrest Using Ensemble-Based Machine Learning.
Computers, informatics, nursing : CIN
May 1, 2024
As of now, a model for predicting the survival of patients with out-of-hospital cardiac arrest has not been established. This study aimed to develop a model for identifying predictors of survival over time in patients with out-of-hospital cardiac arr...
Machine learning approach for prediction of outcomes in anticoagulated patients with atrial fibrillation.
International journal of cardiology
Apr 23, 2024
BACKGROUND: The accuracy of available prediction tools for clinical outcomes in patients with atrial fibrillation (AF) remains modest. Machine Learning (ML) has been used to predict outcomes in the AF population, but not in a population entirely on a...
Identifying Bladder Phenotypes After Spinal Cord Injury With Unsupervised Machine Learning: A New Way to Examine Urinary Symptoms and Quality of Life.
The Journal of urology
Apr 16, 2024
PURPOSE: Patients with spinal cord injuries (SCIs) experience variable urinary symptoms and quality of life (QOL). Our objective was to use machine learning to identify bladder-relevant phenotypes after SCI and assess their association with urinary s...
Predicting ischemic stroke patients' prognosis changes using machine learning in a nationwide stroke registry.
Medical & biological engineering & computing
Apr 5, 2024
Accurately predicting the prognosis of ischemic stroke patients after discharge is crucial for physicians to plan for long-term health care. Although previous studies have demonstrated that machine learning (ML) shows reasonably accurate stroke outco...
Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study.
European journal of pediatrics
Mar 30, 2024
Early prediction of surgical necrotizing enterocolitis (sNEC) in preterm infants is important. However, owing to the complexity of the disease, identifying infants with NEC at a high risk for surgical intervention is difficult. We developed a machine...
Using machine learning to predict outcomes of patients with blunt traumatic aortic injuries.
The journal of trauma and acute care surgery
Mar 29, 2024
BACKGROUND: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to d...
Building large-scale registries from unstructured clinical notes using a low-resource natural language processing pipeline.
Artificial intelligence in medicine
Mar 22, 2024
Building clinical registries is an important step in clinical research and improvement of patient care quality. Natural Language Processing (NLP) methods have shown promising results in extracting valuable information from unstructured clinical notes...
Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.
Clinical orthopaedics and related research
Mar 12, 2024
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling a...
A practical guide to the development and deployment of deep learning models for the orthopaedic surgeon: Part III, focus on registry creation, diagnosis, and data privacy.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Mar 1, 2024
Deep learning is a subset of artificial intelligence (AI) with enormous potential to transform orthopaedic surgery. As has already become evident with the deployment of Large Language Models (LLMs) like ChatGPT (OpenAI Inc.), deep learning can rapidl...
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