AIMC Topic: Decision Support Techniques

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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...
Predictive Value of Tests Cause of Death Heart Failure Patient Admission Intensive Care Units Female Risk Factors Aged Aged, 80 and over Male Middle Aged Risk Assessment Blood Glucose Time Factors Hyperglycemia Chronic Disease Machine Learning Decision Support Techniques Databases, Factual Biomarkers Prognosis Retrospective Studies Humans
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Deep-learning prediction of cardiovascular outcomes from routine retinal images in individuals with type 2 diabetes.

Cardiovascular diabetology Jan 2, 2025
BACKGROUND: Prior studies have demonstrated an association between retinal vascular features and cardiovascular disease (CVD), however most studies have only evaluated a few simple parameters at a time. Our aim was to determine whether a deep-learnin...
Decision Support Techniques Prognosis Female Reproducibility of Results Risk Factors Aged Humans Diabetic Retinopathy Diabetes Mellitus, Type 2 Predictive Value of Tests Heart Disease Risk Factors Image Interpretation, Computer-Assisted Photography Retinal Vessels Male Cardiovascular Diseases Middle Aged Risk Assessment Deep Learning Time Factors
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Prediction of futile recanalisation after endovascular treatment in acute ischaemic stroke: development and validation of a hybrid machine learning model.

Stroke and vascular neurology Dec 30, 2024
BACKGROUND: Identification of futile recanalisation following endovascular therapy (EVT) in patients with acute ischaemic stroke is both crucial and challenging. Here, we present a novel risk stratification system based on hybrid machine learning met...
Humans Machine Learning Decision Support Techniques Databases, Factual Aged, 80 and over Male Middle Aged Risk Assessment Time Factors Treatment Outcome Prospective Studies Clinical Decision-Making Female Reproducibility of Results Risk Factors Aged Predictive Value of Tests Ischemic Stroke Endovascular Procedures Medical Futility
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Predicting lack of clinical improvement following varicose vein ablation using machine learning.

Journal of vascular surgery. Venous and lymphatic disorders Dec 26, 2024
OBJECTIVE: Varicose vein ablation is generally indicated in patients with active/healed venous ulcers. However, patient selection for intervention in individuals without venous ulcers is less clear. Tools that predict lack of clinical improvement (LC...
Humans Treatment Outcome Machine Learning Predictive Value of Tests Ablation Techniques Varicose Veins Aged Male Middle Aged Risk Assessment Decision Support Techniques Postoperative Complications Databases, Factual Time Factors Retrospective Studies Clinical Decision-Making Female Risk Factors
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Machine Learning Model for Risk Prediction of Prolonged Intensive Care Unit in Patients Receiving Intra-aortic Balloon Pump Therapy during Coronary Artery Bypass Graft Surgery.

Journal of cardiovascular translational research Dec 24, 2024
This study aimed to construct machine learning models and predict prolonged intensive care units (ICU) stay in patients receiving perioperative intra-aortic balloon pump (IABP) therapy during cardiac surgery. 236 patients were divided into the normal...
Humans Machine Learning Decision Support Techniques Predictive Value of Tests Coronary Artery Bypass Intra-Aortic Balloon Pumping Male Middle Aged Retrospective Studies Risk Assessment Intensive Care Units Length of Stay Female Time Factors Reproducibility of Results Treatment Outcome Risk Factors Aged
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Screening prediction models using artificial intelligence for moderate-to-severe obstructive sleep apnea in patients with acute ischemic stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Dec 24, 2024
BACKGROUND: Obstructive sleep apnea (OSA) is common after stroke. Still, routine screening of OSA with polysomnography (PSG) is often unfeasible in clinical practice, primarily because of how limited resources are and the physical condition of patien...
Male Middle Aged Risk Assessment Severity of Illness Index Predictive Value of Tests Ischemic Stroke Sleep Apnea, Obstructive Sleep Polysomnography Artificial Intelligence Machine Learning Decision Support Techniques Female Humans Risk Factors Aged
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Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.

Journal of cardiovascular electrophysiology Dec 23, 2024
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates partly due to the considerable heterogeneity within the patient population. Identifying distinct patient phenotypes based on post-ablation prognosis co...
Action Potentials Predictive Value of Tests Atrial Fibrillation Heart Rate Catheter Ablation Recurrence Middle Aged Risk Assessment Time Factors Treatment Outcome Cluster Analysis Humans Machine Learning Decision Support Techniques Phenotype Female Reproducibility of Results Risk Factors Aged Male
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Machine learning based prediction model for bile leak following hepatectomy for liver cancer.

HPB : the official journal of the International Hepato Pancreato Biliary Association Dec 20, 2024
OBJECTIVE: We sought to develop a machine learning (ML) preoperative model to predict bile leak following hepatectomy for primary and secondary liver cancer.
Predictive Value of Tests Hepatectomy Anastomotic Leak Cholangiocarcinoma Humans Male Decision Support Techniques Machine Learning Middle Aged Databases, Factual Risk Assessment Retrospective Studies Liver Neoplasms Female Carcinoma, Hepatocellular Risk Factors Aged
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Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

BMC cardiovascular disorders Dec 20, 2024
INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalies, constitutes a significant contributor to the burden of non-communicable diseases, highlighting the critical need for improved risk assessment tools...
Cardiac Surgical Procedures Heart Defects, Congenital Adolescent Time Factors Child, Preschool Child Treatment Outcome Predictive Value of Tests Humans Artificial Intelligence Decision Support Techniques Female Infant, Newborn Risk Factors Young Adult Adult Male Risk Assessment Postoperative Complications Infant
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Machine learning to predict the decision to perform surgery in hepatic echinococcosis.

HPB : the official journal of the International Hepato Pancreato Biliary Association Dec 19, 2024
BACKGROUND: Cystic echinococcosis (CE) is a significant public health issue, primarily affecting the liver. While several management strategies exist, there is a lack of predictive tools to guide surgical decisions for hepatic CE. This study aimed to...
Decision Trees Predictive Value of Tests Hepatectomy Echinococcosis, Hepatic Female Humans Aged Machine Learning Adult Decision Support Techniques Male Retrospective Studies Middle Aged Clinical Decision-Making Risk Assessment
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