AIMC Topic: Hospitalization

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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
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...

Factors associated with COVID-19 lethality in a hospital in the Cajamarca region in Peru.

Revista peruana de medicina experimental y salud publica
OBJECTIVE.: To identify the clinical and epidemiological characteristics related to lethality in patients hospitalized for COVID-19 at the Simón Bolívar Hospital in Cajamarca, during June-August 2020.

A Broad Learning System to Predict the 28-Day Mortality of Patients Hospitalized with Community-Acquired Pneumonia: A Case-Control Study.

Computational and mathematical methods in medicine
This study was to conduct a model based on the broad learning system (BLS) for predicting the 28-day mortality of patients hospitalized with community-acquired pneumonia (CAP). A total of 1,210 eligible CAP cases from Chifeng Municipal Hospital were ...

Estimation and Prediction of Hospitalization and Medical Care Costs Using Regression in Machine Learning.

Journal of healthcare engineering
Medical costs are one of the most common recurring expenses in a person's life. Based on different research studies, BMI, ageing, smoking, and other factors are all related to greater personal medical care costs. The estimates of the expenditures of ...

Evolution of hospitalized patient characteristics through the first three COVID-19 waves in Paris area using machine learning analysis.

PloS one
Characteristics of patients at risk of developing severe forms of COVID-19 disease have been widely described, but very few studies describe their evolution through the following waves. Data was collected retrospectively from a prospectively maintain...

On the explainability of hospitalization prediction on a large COVID-19 patient dataset.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We develop various AI models to predict hospitalization on a large (over 110k) cohort of COVID-19 positive-tested US patients, sourced from March 2020 to February 2021. Models range from Random Forest to Neural Network (NN) and Time Convolutional NN,...

Machine learning-based prediction of critical illness in children visiting the emergency department.

PloS one
OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have ...

Framework for Integrating Equity Into Machine Learning Models: A Case Study.

Chest
Predictive analytic models leveraging machine learning methods increasingly have become vital to health care organizations hoping to improve clinical outcomes and the efficiency of care delivery for all patients. Unfortunately, predictive models coul...