AIMC Topic: Patient Readmission
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A Neurosurgical Readmissions Reduction Program in an Academic Hospital Leveraging Machine Learning, Workflow Analysis, and Simulation.
Applied clinical informatics
Jun 19, 2024
BACKGROUND: Predicting 30-day hospital readmissions is crucial for improving patient outcomes, optimizing resource allocation, and achieving financial savings. Existing studies reporting the development of machine learning (ML) models predictive of ...
Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention.
Scientific reports
Jun 11, 2024
To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive mod...
Classification tree obtained by artificial intelligence for the prediction of heart failure after acute coronary syndromes.
Medicina clinica
May 30, 2024
BACKGROUND: Coronary heart disease is the leading cause of heart failure (HF), and tools are needed to identify patients with a higher probability of developing HF after an acute coronary syndrome (ACS). Artificial intelligence (AI) has proven to be ...
Predicting 1 year readmission for heart failure: A comparative study of machine learning and the LACE index.
ESC heart failure
May 22, 2024
AIMS: There is a lack of tools for accurately identifying the risk of readmission for heart failure in elderly patients with arrhythmia. The aim of this study was to establish and compare the performance of the LACE [length of stay ('L'), acute (emer...
Machine learning models on a web application to predict short-term postoperative outcomes following anterior cervical discectomy and fusion.
BMC musculoskeletal disorders
May 21, 2024
BACKGROUND: The frequency of anterior cervical discectomy and fusion (ACDF) has increased up to 400% since 2011, underscoring the need to preoperatively anticipate adverse postoperative outcomes given the procedure's expanding use. Our study aims to ...
Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits.
Journal of biomedical informatics
May 19, 2024
The increasing prevalence of overcrowding in Emergency Departments (EDs) threatens the effective delivery of urgent healthcare. Mitigation strategies include the deployment of monitoring systems capable of tracking and managing patient disposition to...
Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.
Journal of orthopaedic surgery and research
May 10, 2024
BACKGROUND: The Center for Medicare and Medicaid Services (CMS) imposes payment penalties for readmissions following total joint replacement surgeries. This study focuses on total hip, knee, and shoulder arthroplasty procedures as they account for mo...
The Efficacy of Machine Learning Models for Predicting the Prognosis of Heart Failure: A Systematic Review and Meta-Analysis.
Cardiology
Apr 22, 2024
INTRODUCTION: Heart failure (HF) is a major global public health concern. The application of machine learning (ML) to identify individuals at high risk and enable early intervention is a promising approach for improving HF prognosis. We aim to system...
Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.
BMJ health & care informatics
Apr 22, 2024
BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has...
Machine learning for enhanced prognostication: predicting 30-day outcomes following posterior fossa decompression surgery for Chiari malformation type I in a pediatric cohort.
Journal of neurosurgery. Pediatrics
Apr 12, 2024
OBJECTIVE: Chiari malformation type I (CM-I) is a congenital disorder occurring in 0.1% of the population. In symptomatic cases, surgery with posterior fossa decompression (PFD) is the treatment of choice. Surgery is, however, associated with peri- a...
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