AIMC Topic: Predictive Value of Tests

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The Future of Artificial Intelligence Using Images and Clinical Assessment for Difficult Airway Management.

Anesthesia and analgesia Jan 10, 2025
Artificial intelligence (AI) algorithms, particularly deep learning, are automatic and sophisticated methods that recognize complex patterns in imaging data providing high qualitative assessments. Several machine-learning and deep-learning models usi...
Deep Learning Predictive Value of Tests Airway Management Laryngoscopy Intubation, Intratracheal Humans Artificial Intelligence Machine Learning Forecasting
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Deep learning-based lymph node metastasis status predicts prognosis from muscle-invasive bladder cancer histopathology.

World journal of urology Jan 10, 2025
PURPOSE: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph node metastasis (LNM) status of muscle invasive bladder cancer (MIBC), while validating the prognostic value of the predicted aiN score in MIBC patients...
Female Aged Male Middle Aged Deep Learning Humans Lymphatic Metastasis Urinary Bladder Neoplasms Prognosis Neoplasm Invasiveness Retrospective Studies Predictive Value of Tests
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Machine learning techniques to predict diabetic ketoacidosis and HbA1c above 7% among individuals with type 1 diabetes - A large multi-centre study in Australia and New Zealand.

Nutrition, metabolism, and cardiovascular diseases : NMCD Jan 9, 2025
BACKGROUND AND AIMS: Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.
Humans Female Risk Factors Young Adult Adult Male Middle Aged Machine Learning Decision Support Techniques Prospective Studies Biomarkers Prognosis Risk Assessment Deep Learning Adolescent Diabetes Mellitus, Type 1 Diabetic Ketoacidosis Support Vector Machine Australia Predictive Value of Tests Glycated Hemoglobin New Zealand
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Risk prediction for elderly cognitive impairment by radiomic and morphological quantification analysis based on a cerebral MRA imaging cohort.

European radiology Jan 9, 2025
OBJECTIVE: To establish morphological and radiomic models for early prediction of cognitive impairment associated with cerebrovascular disease (CI-CVD) in an elderly cohort based on cerebral magnetic resonance angiography (MRA).
Retrospective Studies Female Risk Factors Aged Cerebrovascular Disorders Aged, 80 and over Magnetic Resonance Angiography Radiomics Male Risk Assessment Cognitive Dysfunction Cohort Studies Predictive Value of Tests Humans
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Machine Learning Algorithms in Controlled Donation After Circulatory Death Under Normothermic Regional Perfusion: A Graft Survival Prediction Model.

Transplantation Jan 9, 2025
BACKGROUND: Several scores have been developed to stratify the risk of graft loss in controlled donation after circulatory death (cDCD). However, their performance is unsatisfactory in the Spanish population, where most cDCD livers are recovered usin...
Decision Support Techniques Retrospective Studies Female Male Humans Graft Survival Risk Factors Middle Aged Machine Learning Aged Treatment Outcome Risk Assessment Algorithms Adult Predictive Value of Tests Time Factors Liver Transplantation Tissue Donors Perfusion Spain
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Automated stenosis estimation of coronary angiographies using end-to-end learning.

The international journal of cardiovascular imaging Jan 9, 2025
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consumin...
Automation Deep Learning Female Humans Coronary Vessels Predictive Value of Tests Retrospective Studies Reproducibility of Results Coronary Stenosis Coronary Angiography Aged Fractional Flow Reserve, Myocardial Radiographic Image Interpretation, Computer-Assisted Male Coronary Artery Disease Middle Aged Severity of Illness Index
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Multimodal deep learning for predicting in-hospital mortality in heart failure patients using longitudinal chest X-rays and electronic health records.

The international journal of cardiovascular imaging Jan 9, 2025
Amid an aging global population, heart failure has become a leading cause of hospitalization among older people. Its high prevalence and mortality rates underscore the importance of accurate mortality prediction for swift disease progression assessme...
Prognosis Electronic Health Records Female Reproducibility of Results Radiography, Thoracic Risk Factors Time Factors Aged Humans Hospital Mortality Aged, 80 and over Decision Support Techniques Predictive Value of Tests Male Feasibility Studies Middle Aged Heart Failure Risk Assessment Deep Learning
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Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index.

Journal of cardiovascular computed tomography Jan 9, 2025
BACKGROUND: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among...
Computed Tomography Angiography Transcatheter Aortic Valve Replacement Risk Assessment Severity of Illness Index Aged Time Factors Aortic Valve Aged, 80 and over Humans Treatment Outcome Predictive Value of Tests Male Artificial Intelligence Ventricular Function, Left Aortic Valve Stenosis Retrospective Studies Coronary Angiography Stroke Volume Radiographic Image Interpretation, Computer-Assisted Female Risk Factors Automation Atrial Function, Left
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Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer.

Gut and liver Jan 8, 2025
BACKGROUND/AIMS: Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predict...
Neoplasm Staging Retrospective Studies Female Aged Aged, 80 and over Colorectal Neoplasms Male Middle Aged ROC Curve Lymph Nodes Lymphatic Metastasis Predictive Value of Tests Humans Artificial Intelligence Algorithms
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Predicting 28-day all-cause mortality in patients admitted to intensive care units with pre-existing chronic heart failure using the stress hyperglycemia ratio: a machine learning-driven retrospective cohort analysis.

Cardiovascular diabetology Jan 8, 2025
Chronic heart failure (CHF) poses a significant threat to human health. The stress hyperglycemia ratio (SHR) is a novel metric for accurately assessing stress hyperglycemia, which has been correlated with adverse outcomes in various major diseases. H...
Heart Failure Patient Admission Time Factors Hyperglycemia Chronic Disease Predictive Value of Tests Cause of Death Prognosis Retrospective Studies Humans Intensive Care Units Aged Machine Learning Female Decision Support Techniques Aged, 80 and over Risk Factors Databases, Factual Male Biomarkers Middle Aged Risk Assessment Blood Glucose
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