AIMC Topic: Hospitalization
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Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure.
ESC heart failure
Jun 23, 2022
AIMS: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF).
A deep learning based multimodal interaction system for bed ridden and immobile hospital admitted patients: design, development and evaluation.
BMC health services research
Jun 21, 2022
BACKGROUND: Hospital cabins are a part and parcel of the healthcare system. Most patients admitted in hospital cabins reside in bedridden and immobile conditions. Though different kinds of systems exist to aid such patients, most of them focus on spe...
Simplified Machine Learning Models Can Accurately Identify High-Need High-Cost Patients With Inflammatory Bowel Disease.
Clinical and translational gastroenterology
Jun 7, 2022
INTRODUCTION: Hospitalization is the primary driver of inflammatory bowel disease (IBD)-related healthcare costs and morbidity. Traditional prediction models have poor performance at identifying patients at highest risk of unplanned healthcare utiliz...
Prediction of Bronchopneumonia Inpatients' Total Hospitalization Expenses Based on BP Neural Network and Support Vector Machine Models.
Computational and mathematical methods in medicine
May 18, 2022
OBJECTIVE: BP neural network (BPNN) model and support vector machine (SVM) model were used to predict the total hospitalization expenses of patients with bronchopneumonia.
Optimizing discharge after major surgery using an artificial intelligence-based decision support tool (DESIRE): An external validation study.
Surgery
May 4, 2022
BACKGROUND: In the DESIRE study (Discharge aftEr Surgery usIng aRtificial intElligence), we have previously developed and validated a machine learning concept in 1,677 gastrointestinal and oncology surgery patients that can predict safe hospital disc...
Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.
Applied clinical informatics
May 4, 2022
OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital.
Cardiac auscultation predicts mortality in elderly patients admitted for COVID-19.
Hospital practice (1995)
Apr 29, 2022
INTRODUCTION: COVID-19 has had a great impact on the elderly population. All admitted patients underwent cardiac auscultation at the Emergency Department. However, to our knowledge, there is no literature that explains the implications of cardiac aus...
Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network.
BMC anesthesiology
Apr 23, 2022
BACKGROUND: Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), make...
Interpretability Analysis of One-Year Mortality Prediction for Stroke Patients Based on Deep Neural Network.
IEEE journal of biomedical and health informatics
Apr 14, 2022
Clinically, physicians collect the benchmark medical data to establish archives for a stroke patient and then add the follow up data regularly. It has great significance on prognosis prediction for stroke patients. In this paper, we present an interp...
Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization.
The Journal of asthma : official journal of the Association for the Care of Asthma
Apr 7, 2022
OBJECTIVE: Asthma is the most frequent chronic airway illness in preschool children and is difficult to diagnose due to the disease's heterogeneity. This study aimed to investigate different machine learning models and suggested the most effective on...
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