AIMC Topic: Acute Disease

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Prediction of short-term adverse clinical outcomes of acute pulmonary embolism using conventional machine learning and deep Learning based on CTPA images.

Journal of thrombosis and thrombolysis Sep 28, 2024
To explore the predictive value of traditional machine learning (ML) and deep learning (DL) algorithms based on computed tomography pulmonary angiography (CTPA) images for short-term adverse outcomes in patients with acute pulmonary embolism (APE). T...
Middle Aged Deep Learning ROC Curve Predictive Value of Tests Acute Disease Retrospective Studies Female Risk Factors Aged Male Pulmonary Embolism Computed Tomography Angiography Humans Machine Learning Prognosis
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Exploring Heterogeneity in the Cost-Effectiveness of High-Flow Nasal Cannula Therapy in Acutely Ill Children-Insights From the Step-Up First-line Support for Assistance in Breathing in Children Trial Using a Machine Learning Method.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Sep 28, 2024
OBJECTIVES: To investigate heterogeneity in the cost-effectiveness of high-flow nasal cannula (HFNC) therapy compared with continuous positive airway pressure (CPAP) for acutely ill children requiring noninvasive respiratory support.
Cost-Benefit Analysis Quality-Adjusted Life Years United Kingdom Oxygen Inhalation Therapy Continuous Positive Airway Pressure Equivalence Trials as Topic Cannula Child Intensive Care Units, Pediatric Multicenter Studies as Topic Male Randomized Controlled Trials as Topic Acute Disease Infant Humans Adolescent Machine Learning Child, Preschool Female Infant, Newborn
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An Artificial Intelligence Algorithm Integrated into the Clinical Workflow Can Ensure High Quality Acute Intracranial Hemorrhage CT Diagnostic.

Clinical neuroradiology Sep 26, 2024
PURPOSE: Intracranial hemorrhage (ICH) is a life-threatening condition requiring rapid diagnostic and therapeutic action. This study evaluates whether Artificial intelligence (AI) can provide high-quality ICH diagnostics and turnaround times suitable...
Algorithms Tomography, X-Ray Computed Female Aged Sensitivity and Specificity Humans Neural Networks, Computer Artificial Intelligence Workflow Germany Intracranial Hemorrhages Male Middle Aged Pilot Projects Acute Disease
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Machine learning predicts acute respiratory failure in pancreatitis patients: A retrospective study.

International journal of medical informatics Sep 14, 2024
PURPOSE: The purpose of the research is to design an algorithm to predict the occurrence of acute respiratory failure (ARF) in patients with acute pancreatitis (AP).
Bayes Theorem Respiratory Insufficiency Pancreatitis Algorithms Retrospective Studies Female Aged Adult Humans Male Machine Learning Middle Aged ROC Curve Logistic Models Acute Disease
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Machine learning analysis of contrast-enhanced ultrasound (CEUS) for the diagnosis of acute graft dysfunction in kidney transplant recipients.

Medical ultrasonography Sep 4, 2024
AIM: The aim of the study was to develop machine learning algorithms (MLA) for diagnosing acute graft dysfunction (AGD) in kidney transplant recipients based on contrast-enhanced ultrasound (CEUS) analysis of the graft.Materials and methods: This pro...
Kidney Transplantation Prospective Studies Female Reproducibility of Results Adult Humans Machine Learning Kidney Sensitivity and Specificity Contrast Media Male Acute Disease Middle Aged Image Enhancement Postoperative Complications Primary Graft Dysfunction Ultrasonography
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Prediction of mortality events of patients with acute heart failure in intensive care unit based on deep neural network.

Computer methods and programs in biomedicine Aug 30, 2024
BACKGROUND: Acute heart failure (AHF) in the intensive care unit (ICU) is characterized by its criticality, rapid progression, complex and changeable condition, and its pathophysiological process involves the interaction of multiple organs and system...
Deep Learning Hospital Mortality Acute Disease Heart Failure Data Mining Risk Factors Databases, Factual Aged Prognosis Humans Male Intensive Care Units Middle Aged Neural Networks, Computer Electronic Health Records Machine Learning Female Algorithms
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Meta-analysis of the effectiveness of early endoscopic treatment of Acute biliary pancreatitis based on lightweight deep learning model.

BMC gastroenterology Aug 28, 2024
BACKGROUND: Acute biliary pancreatitis (ABP) is a clinical common acute abdomen. After the first pancreatitis, relapse rate is high, which seriously affects human life and health and causes great economic burdens to family and society. According to a...
Humans Deep Learning Length of Stay Treatment Outcome Operative Time Acute Disease Cholangiopancreatography, Endoscopic Retrograde Time-to-Treatment Pancreatitis
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Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.

Journal of clinical gastroenterology Aug 1, 2024
BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined w...
Humans Severity of Illness Index Female Pancreatitis Machine Learning ROC Curve Aged Algorithms Logistic Models Adult Predictive Value of Tests Biomarkers Male Acute Disease Retrospective Studies Middle Aged Tomography, X-Ray Computed
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Comparison of machine learning and conventional statistical modeling for predicting readmission following acute heart failure hospitalization.

American heart journal Jul 31, 2024
INTRODUCTION: Developing accurate models for predicting the risk of 30-day readmission is a major healthcare interest. Evidence suggests that models developed using machine learning (ML) may have better discrimination than conventional statistical mo...
Risk Assessment Hospitalization Humans Patient Readmission Ontario Aged Machine Learning Models, Statistical Aged, 80 and over Retrospective Studies Acute Disease Male Female Heart Failure Middle Aged
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Identification of severe acute pediatric asthma phenotypes using unsupervised machine learning.

Pediatric pulmonology Jul 29, 2024
RATIONALE: More targeted management of severe acute pediatric asthma could improve clinical outcomes.
Adolescent Hospitalization Humans Acute Disease Asthma Child, Preschool Phenotype Child Male Retrospective Studies Cluster Analysis Severity of Illness Index Female Unsupervised Machine Learning
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