AIMC Topic: Patient Readmission
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Evaluating the Predictive Features of Person-Centric Knowledge Graph Embeddings: Unfolding Ablation Studies.
Studies in health technology and informatics
Aug 22, 2024
Developing novel predictive models with complex biomedical information is challenging due to various idiosyncrasies related to heterogeneity, standardization or sparseness of the data. We previously introduced a person-centric ontology to organize in...
Predicting the risk of mortality and rehospitalization in heart failure patients: A retrospective cohort study by machine learning approach.
Clinical cardiology
May 1, 2024
Minimally invasive surgery for clinical T4 non-small-cell lung cancer: national trends and outcomes.
European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
Mar 1, 2024
OBJECTIVES: Recent randomized data support the perioperative benefits of minimally invasive surgery (MIS) for non-small-cell lung cancer (NSCLC). Its utility for cT4 tumours remains understudied. We, therefore, sought to analyse national trends and o...
Interpretable Machine Learning Models Using Peripheral Immune Cells to Predict 90-Day Readmission or Mortality in Acute Heart Failure Patients.
Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Jan 1, 2024
BACKGROUND: Acute heart failure (AHF) carries a grave prognosis, marked by high readmission and mortality rates within 90 days post-discharge. This underscores the urgent need for enhanced care transitions, early monitoring, and precise interventions...
Improving Cardiology-Rehospitalization Prediction Through the Synergy of Process Mining and Deep Learning: An Innovative Approach.
Studies in health technology and informatics
Oct 20, 2023
Nowadays, hospitals are facing the need for an accurate prediction of rehospitalizations. Rehospitalizations, indeed, represent both a high financial burden for the hospital and a proxy measure of care quality. The current work aims to address such a...
[Comparison of the predictive performance of Logistic regression, BP neural network and support vector machine model for the risk of acute exacerbation of readmission in elderly patients with chronic obstructive pulmonary disease within 30 days].
Zhonghua wei zhong bing ji jiu yi xue
Aug 1, 2022
OBJECTIVE: To compare the effectiveness of Logistic regression, BP neural network and support vector machine models in the prediction of 30-day risk of readmission in elderly patients with an exacerbation of chronic obstructive pulmonary disease (COP...
Hospital Readmission Prediction via Keyword Extraction and Sentiment Analysis on Clinical Notes.
Studies in health technology and informatics
Jun 29, 2022
Unplanned hospital readmission is a problem that affects hospitals worldwide and is due to different factors. The identification of those factors can help determine which patients are at greater risk of hospital readmission for early intervention. Ou...
Predicting Readmission Following Hospital Treatment for Patients with Alcohol Related Diagnoses in an Australian Regional Health District.
Studies in health technology and informatics
Jun 6, 2022
This study aims to investigate the prediction of hospital readmission of alcohol use disorder patients within 28 days of discharge and compare the performance of six machine learning methods i.e., random forest (RF), logistics regression, linear supp...
Deep learning-based prediction of heart failure rehospitalization during 6, 12, 24-month follow-ups in patients with acute myocardial infarction.
Health informatics journal
Jan 1, 2022
Heart failure is a clinical syndrome that occurs when the heart is too weak or stiff and cannot pump enough blood that our body needs. It is one of the most expensive diseases due to frequent hospitalizations and emergency room visits. Reducing unnec...
A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.
Journal of the American Medical Informatics Association : JAMIA
Mar 18, 2021
Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been suggested to predict unplanned hospital readmissions. These ML models were often specifically trained on ...
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