AIMC Topic: Decision Support Techniques

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A Predictive Model Integrating AI Recognition Technology and Biomarkers for Lung Nodule Assessment.

The Thoracic and cardiovascular surgeon Nov 26, 2024
BACKGROUND:  Lung cancer is the most prevalent and lethal cancer globally, necessitating accurate differentiation between benign and malignant pulmonary nodules to guide treatment decisions. This study aims to develop a predictive model that integrat...
Neoplasm Invasiveness Predictive Value of Tests Humans Artificial Intelligence Decision Support Techniques Retrospective Studies Biomarkers, Tumor Male Middle Aged Tomography, X-Ray Computed Lung Neoplasms Female Multiple Pulmonary Nodules Reproducibility of Results Solitary Pulmonary Nodule Risk Factors Aged
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Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning.

Cardiovascular diabetology Nov 26, 2024
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
Reproducibility of Results Risk Factors Aged Aged, 80 and over Male Middle Aged Prognosis Retrospective Studies Critical Illness Intensive Care Units Female Humans Atrial Fibrillation Machine Learning Glycemic Control Decision Support Techniques Risk Assessment Databases, Factual Biomarkers Blood Glucose Time Factors Hospital Mortality Predictive Value of Tests Cause of Death
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Artificial Intelligence in Diagnosing and Managing Vascular Surgery Patients: An Experimental Study Using the GPT-4 Model.

Annals of vascular surgery Nov 24, 2024
BACKGROUND: The introduction of artificial intelligence (AI) has led to groundbreaking advancements across many scientific fields. Machine learning algorithms have enabled AI models to learn, adapt, and solve complex problems in previously unimaginab...
Humans Artificial Intelligence Machine Learning Decision Support Techniques Clinical Decision-Making Predictive Value of Tests Natural Language Processing Vascular Surgical Procedures
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Predicting Short-Term Mortality after Endovascular Aortic Repair Using Machine Learning-Based Decision Tree Analysis.

Annals of vascular surgery Nov 22, 2024
BACKGROUND: Endovascular aneurysm repair (EVAR) has revolutionized the treatment of abdominal aortic aneurysms by offering a less invasive alternative to open surgery. Understanding the factors that influence patient outcomes, particularly for high-r...
Time Factors Humans Treatment Outcome Machine Learning Decision Trees Predictive Value of Tests Aortic Aneurysm, Abdominal Nutritional Status Blood Vessel Prosthesis Implantation Endovascular Procedures Endovascular Aneurysm Repair Risk Factors Aged Decision Support Techniques Aged, 80 and over Retrospective Studies Male Clinical Decision-Making Middle Aged Female Risk Assessment Reproducibility of Results
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Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

Annals of vascular surgery Nov 22, 2024
BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered ...
Treatment Outcome Predictive Value of Tests Wakefulness Carotid Stenosis Neurologic Examination Endarterectomy, Carotid Aged, 80 and over Male Middle Aged Risk Assessment Case-Control Studies Intraoperative Neurophysiological Monitoring Retrospective Studies Female Reproducibility of Results Humans Risk Factors Machine Learning Aged Decision Support Techniques
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Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.

Cardiovascular diabetology Nov 15, 2024
BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop ...
Risk Assessment China Time Factors Hospital Mortality Hypertension Age Factors Female Risk Factors Aged Aged, 80 and over Male Predictive Value of Tests Heart Failure Humans Machine Learning Decision Support Techniques Databases, Factual Prognosis Retrospective Studies
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Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.

European respiratory review : an official journal of the European Respiratory Society Nov 13, 2024
BACKGROUND: Asthma exacerbations in children pose a significant burden on healthcare systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) offers the potential for enhanced prediction models.
Adolescent Risk Factors Humans Child, Preschool Hospitalization Machine Learning Patient Admission Child Asthma Decision Support Techniques Age Factors Male Prognosis Predictive Value of Tests Risk Assessment Female Emergency Service, Hospital Disease Progression
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Assessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography.

The international journal of cardiovascular imaging Nov 8, 2024
PURPOSE: This study aimed to evaluate the efficacy of the Chat Generative Pre-trained Transformer (ChatGPT) in guiding the need for invasive coronary angiography (ICA) in high-risk non-ST-elevation (NSTE) acute coronary syndrome (ACS) patients based ...
Clinical Decision-Making Female Reproducibility of Results Risk Factors Aged Male Humans Artificial Intelligence Decision Support Techniques Prospective Studies Middle Aged Coronary Angiography Risk Assessment Radiographic Image Interpretation, Computer-Assisted Non-ST Elevated Myocardial Infarction Acute Coronary Syndrome Predictive Value of Tests Computed Tomography Angiography Double-Blind Method
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Machine Learning Model for Predicting Risk Factors of Prolonged Length of Hospital Stay in Patients with Aortic Dissection: a Retrospective Clinical Study.

Journal of cardiovascular translational research Oct 10, 2024
The length of hospital stay (LOS) is crucial for assessing medical service quality. This study aimed to develop machine learning models for predicting risk factors of prolonged LOS in patients with aortic dissection (AD). The data of 516 AD patients ...
Humans Machine Learning Decision Support Techniques Retrospective Studies Risk Assessment Length of Stay Time Factors Predictive Value of Tests Female Aortic Dissection Risk Factors Aortic Aneurysm Aged Adult Male Middle Aged
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Using novel machine learning tools to predict optimal discharge following transcatheter aortic valve replacement.

Archives of cardiovascular diseases Oct 5, 2024
BACKGROUND: Although transcatheter aortic valve replacement has emerged as an alternative to surgical aortic valve replacement, it requires extensive healthcare resources, and optimal length of hospital stay has become increasingly important. This st...
Patient Discharge Transcatheter Aortic Valve Replacement Time Factors Machine Learning United States Decision Support Techniques Treatment Outcome Databases, Factual Aortic Valve Stenosis Humans Retrospective Studies Risk Factors Aortic Valve Neural Networks, Computer Aged Clinical Decision-Making Predictive Value of Tests Aged, 80 and over Female Male Risk Assessment Length of Stay
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