AIMC Topic: Registries
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Machine learning for prediction of ventricular arrhythmia episodes from intracardiac electrograms of automatic implantable cardioverter-defibrillators.
Heart rhythm
May 24, 2024
BACKGROUND: Despite effectiveness of the implantable cardioverter-defibrillator (ICD) in saving patients with life-threatening ventricular arrhythmias (VAs), the temporal occurrence of VA after ICD implantation is unpredictable.
Machine learning algorithms using national registry data to predict loss to follow-up during tuberculosis treatment.
BMC public health
May 23, 2024
BACKGROUND: Identifying patients at increased risk of loss to follow-up (LTFU) is key to developing strategies to optimize the clinical management of tuberculosis (TB). The use of national registry data in prediction models may be a useful tool to in...
Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.
BMC pulmonary medicine
May 23, 2024
BACKGROUND: Mortality prediction in interstitial lung disease (ILD) poses a significant challenge to clinicians due to heterogeneity across disease subtypes. Currently, forced vital capacity (FVC) and Gender, Age, and Physiology (GAP) score are the t...
Machine learning-based model to predict delirium in patients with advanced cancer treated with palliative care: a multicenter, patient-based registry cohort.
Scientific reports
May 20, 2024
This study aimed to present a new approach to predict to delirium admitted to the acute palliative care unit. To achieve this, this study employed machine learning model to predict delirium in patients in palliative care and identified the significan...
Machine Learning-Based Mortality Prediction in Chronic Kidney Disease among Heart Failure Patients: Insights and Outcomes from the Jordanian Heart Failure Registry.
Medicina (Kaunas, Lithuania)
May 19, 2024
Heart failure (HF) is a prevalent and debilitating condition that imposes a significant burden on healthcare systems and adversely affects the quality of life of patients worldwide. Comorbidities such as chronic kidney disease (CKD), arterial hypert...
Development of interpretable machine learning models to predict in-hospital prognosis of acute heart failure patients.
ESC heart failure
May 15, 2024
AIMS: In recent years, there has been remarkable development in machine learning (ML) models, showing a trend towards high prediction performance. ML models with high prediction performance often become structurally complex and are frequently perceiv...
Risk Factors for Perinatal Arterial Ischemic Stroke: A Machine Learning Approach.
Neurology
May 15, 2024
BACKGROUND AND OBJECTIVES: Perinatal arterial ischemic stroke (PAIS) is a focal vascular brain injury presumed to occur between the fetal period and the first 28 days of life. It is the leading cause of hemiparetic cerebral palsy. Multiple maternal, ...
Systematic screening by a heart team and a machine learning approach contribute to unraveling novel risk factors in revascularization candidates with complex coronary artery disease.
Polish archives of internal medicine
May 13, 2024
INTRODUCTION: The baseline characteristics affecting mortality following percutaneous or surgical revascularization in patients with left main and / or 3‑vessel coronary artery disease (CAD) observed in real‑world practice differ from those establish...
Developing machine learning models to predict multi-class functional outcomes and death three months after stroke in Sweden.
PloS one
May 13, 2024
Globally, stroke is the third-leading cause of mortality and disability combined, and one of the costliest diseases in society. More accurate predictions of stroke outcomes can guide healthcare organizations in allocating appropriate resources to imp...
What do you think caused your ALS? An analysis of the CDC national amyotrophic lateral sclerosis patient registry qualitative risk factor data using artificial intelligence and qualitative methodology.
Amyotrophic lateral sclerosis & frontotemporal degeneration
May 8, 2024
OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is an incurable, progressive neurodegenerative disease with a significant health burden and poorly understood etiology. This analysis assessed the narrative responses from 3,061 participants in the Cente...
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