AIMC Topic: Risk Factors

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Systematic evaluation of machine learning models for postoperative surgical site infection prediction.

PloS one Dec 12, 2024
BACKGROUND: Surgical site infections (SSIs) lead to increased mortality and morbidity, as well as increased healthcare costs. Multiple models for the prediction of this serious surgical complication have been developed, with an increasing use of mach...
Humans Machine Learning Risk Factors Surgical Wound Infection
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Residual risk prediction in anticoagulated patients with atrial fibrillation using machine learning: A report from the GLORIA-AF registry phase II/III.

European journal of clinical investigation Dec 11, 2024
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
Humans Atrial Fibrillation Machine Learning Algorithms Ischemic Attack, Transient Thromboembolism Logistic Models Ischemic Stroke Area Under Curve Anticoagulants Myocardial Infarction Thrombosis Male Administration, Oral Middle Aged Registries Risk Assessment Stroke ROC Curve Female Risk Factors Aged Aged, 80 and over
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Machine Learning-Based Prediction for In-Hospital Mortality After Acute Intracerebral Hemorrhage Using Real-World Clinical and Image Data.

Journal of the American Heart Association Dec 10, 2024
BACKGROUND: Machine learning (ML) techniques are widely employed across various domains to achieve accurate predictions. This study assessed the effectiveness of ML in predicting early mortality risk among patients with acute intracerebral hemorrhage...
Risk Assessment Hospital Mortality ROC Curve Cerebral Hemorrhage Aged Aged, 80 and over Male Middle Aged Predictive Value of Tests Acute Disease Humans Machine Learning Prognosis Retrospective Studies Tomography, X-Ray Computed Female Risk Factors
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From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management.

Hamostaseologie Dec 10, 2024
The high incidence of venous thromboembolism (VTE) globally and the morbidity and mortality burden associated with the disease make it a pressing issue. Machine learning (ML) can improve VTE prevention, detection, and treatment. The ability of this n...
Venous Thromboembolism Machine Learning Algorithms Risk Factors Anticoagulants Humans
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Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.

Medical & biological engineering & computing Dec 9, 2024
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...
Female Risk Factors Aged Male Arthroplasty, Replacement, Knee Humans Reoperation Machine Learning Middle Aged Risk Assessment
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Prediction of Two Year Survival Following Elective Repair of Abdominal Aortic Aneurysms at A Single Centre Using A Random Forest Classification Algorithm.

European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery Dec 9, 2024
OBJECTIVE: The decision to electively repair an abdominal aortic aneurysm (AAA) involves balancing the risk of rupture, peri-procedural death, and life expectancy. Random forest classifiers (RFCs) are powerful machine learning algorithms. The aim of ...
Risk Factors Aged Aged, 80 and over Male Machine Learning Algorithms Retrospective Studies Female Predictive Value of Tests Aortic Aneurysm, Abdominal Elective Surgical Procedures Middle Aged Random Forest Risk Assessment Endovascular Procedures Time Factors Treatment Outcome Humans
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Impact of Inflammation After Cardiac Surgery on 30-Day Mortality and Machine Learning Risk Prediction.

Journal of cardiothoracic and vascular anesthesia Dec 9, 2024
OBJECTIVES: To investigate the impact of systemic inflammatory response syndrome (SIRS) on 30-day mortality following cardiac surgery and develop a machine learning model to predict SIRS.
Postoperative Complications Cohort Studies Systemic Inflammatory Response Syndrome Predictive Value of Tests Cardiac Surgical Procedures Aged Male Middle Aged Risk Assessment Machine Learning Retrospective Studies Female Risk Factors Humans
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Advancing personalised care in atrial fibrillation and stroke: The potential impact of AI from prevention to rehabilitation.

Trends in cardiovascular medicine Dec 7, 2024
Atrial fibrillation (AF) is a complex condition caused by various underlying pathophysiological disorders and is the most common heart arrhythmia worldwide, affecting 2 % of the European population. This prevalence increases with age, imposing signif...
Machine Learning Decision Support Techniques Precision Medicine Risk Factors Risk Assessment Humans Artificial Intelligence Atrial Fibrillation Treatment Outcome Stroke Rehabilitation Recovery of Function Predictive Value of Tests Stroke
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A machine learning-based risk score for prediction of mechanical ventilation in children with dengue shock syndrome: A retrospective cohort study.

PloS one Dec 6, 2024
BACKGROUND: Patients with severe dengue who develop severe respiratory failure requiring mechanical ventilation (MV) support have significantly increased mortality rates. This study aimed to develop a robust machine learning-based risk score to predi...
Risk Factors Child, Preschool Male Humans Child Infant Machine Learning Respiratory Insufficiency Respiration, Artificial Retrospective Studies Severe Dengue Female
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Prediction of undernutrition and identification of its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.

PloS one Dec 6, 2024
BACKGROUND AND OBJECTIVES: Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. Thus, the objectives of this study are to develop an appropriate model for predicting ...
Infant, Newborn Humans Risk Factors Cross-Sectional Studies Machine Learning Male Malnutrition Algorithms Bangladesh Female Infant Child Nutrition Disorders Growth Disorders Thinness Child, Preschool Logistic Models
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