AIMC Topic: Decision Support Techniques

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Developing a decision support tool to predict delayed discharge from hospitals using machine learning.

BMC health services research Jan 11, 2025
BACKGROUND: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital...
Patient Discharge Nova Scotia Female Aged Adult Humans Male Neural Networks, Computer Middle Aged Machine Learning Length of Stay Decision Support Techniques
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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 %.
Australia Female Predictive Value of Tests Risk Factors Glycated Hemoglobin Humans Young Adult New Zealand Adult Machine Learning Male Decision Support Techniques Risk Assessment Middle Aged Prospective Studies Deep Learning Biomarkers Adolescent Prognosis Diabetes Mellitus, Type 1 Diabetic Ketoacidosis Support Vector Machine
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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...
Algorithms Decision Support Techniques Retrospective Studies Female Graft Survival Humans Risk Factors Adult Machine Learning Treatment Outcome Aged Male Predictive Value of Tests Middle Aged Liver Transplantation Risk Assessment Perfusion Time Factors Spain Tissue Donors
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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...
Predictive Value of Tests Feasibility Studies Middle Aged Heart Failure Risk Assessment Radiography, Thoracic Humans Deep Learning Decision Support Techniques Time Factors Female Prognosis Hospital Mortality Reproducibility of Results Electronic Health Records Risk Factors Aged Aged, 80 and over Male
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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...
Cause of Death Heart Failure Patient Admission Risk Assessment Blood Glucose Time Factors Hyperglycemia Chronic Disease Predictive Value of Tests Decision Support Techniques Databases, Factual Biomarkers Prognosis Retrospective Studies Intensive Care Units Female Risk Factors Aged Aged, 80 and over Male Middle Aged Humans Machine Learning
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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...
Humans Diabetic Retinopathy Decision Support Techniques Cardiovascular Diseases Middle Aged Risk Assessment Deep Learning Time Factors Diabetes Mellitus, Type 2 Prognosis Female Reproducibility of Results Risk Factors Aged Male Predictive Value of Tests Heart Disease Risk Factors Image Interpretation, Computer-Assisted Photography Retinal Vessels
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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...
Female Reproducibility of Results Risk Factors Aged Aged, 80 and over Male Middle Aged Risk Assessment Time Factors Treatment Outcome Predictive Value of Tests Ischemic Stroke Humans Machine Learning Decision Support Techniques Databases, Factual Endovascular Procedures Prospective Studies Medical Futility Clinical Decision-Making
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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...
Clinical Decision-Making Risk Assessment Humans Varicose Veins Postoperative Complications Machine Learning Female Time Factors Decision Support Techniques Risk Factors Treatment Outcome Databases, Factual Aged Predictive Value of Tests Retrospective Studies Male Ablation Techniques Middle Aged
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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 Time Factors Treatment Outcome Risk Factors Predictive Value of Tests Aged Coronary Artery Bypass Machine Learning Male Intra-Aortic Balloon Pumping Decision Support Techniques Middle Aged Retrospective Studies Risk Assessment Intensive Care Units Length of Stay Female Reproducibility of Results
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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...
Predictive Value of Tests Ischemic Stroke Sleep Apnea, Obstructive Sleep Polysomnography Humans Risk Factors Artificial Intelligence Aged Machine Learning Male Decision Support Techniques Middle Aged Female Risk Assessment Severity of Illness Index
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