AIMC Topic: Hospitalization
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Comprehensive Machine Learning-Based Prediction Model for Delirium Risk in Older Patients with Dementia: Risk Factors Identification.
Clinical interventions in aging
Jan 1, 2025
BACKGROUND: Delirium superimposed on dementia (DSD) is a severe complication in older adults with dementia, marked by fluctuating cognition, inattention, and altered consciousness. Detection is challenging due to symptom overlap, yet it contributes t...
Proactive care management of AI-identified at-risk patients decreases preventable admissions.
The American journal of managed care
Nov 1, 2024
OBJECTIVES: We assessed whether proactive care management for artificial intelligence (AI)-identified at-risk patients reduced preventable emergency department (ED) visits and hospital admissions (HAs).
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis.
Briefings in bioinformatics
Sep 23, 2024
We sought to develop and validate a machine learning (ML) model for predicting multidimensional frailty based on clinical and laboratory data. Moreover, an explainable ML model utilizing SHapley Additive exPlanations (SHAP) was constructed. This stud...
Antiviral Effectiveness, Clinical Outcomes, and Artificial Intelligence Imaging Analysis for Hospitalized COVID-19 Patients Receiving Antivirals.
Influenza and other respiratory viruses
Sep 1, 2024
INTRODUCTION: There is still a lack of clinical evidence comprehensively evaluating the effectiveness of antiviral treatments for COVID-19 hospitalized patients.
Artificial Intelligence
Pandemics
COVID-19
Retrospective Studies
Humans
Aged
Adult
Male
Middle Aged
Lung
Tomography, X-Ray Computed
Female
SARS-CoV-2
Hospitalization
Ritonavir
COVID-19 Drug Treatment
Betacoronavirus
Pneumonia, Viral
Antiviral Agents
Treatment Outcome
Drug Combinations
Coronavirus Infections
Machine Learning to Predict the Risk of Malnutrition in Hospitalized Patients with Pneumonia and Analysis of Related Prognostic Factor.
Studies in health technology and informatics
Aug 22, 2024
This study explored machine learning's potential in predicting the nutritional status and outcomes for pneumonia patients. It focused on 4,368 patients in a Taiwan medical center from Jan 2016 to Feb 2022, excluding ICU cases. The average age was 77....
Drug Burden Index Is a Modifiable Predictor of 30-Day Hospitalization in Community-Dwelling Older Adults With Complex Care Needs: Machine Learning Analysis of InterRAI Data.
The journals of gerontology. Series A, Biological sciences and medical sciences
Aug 1, 2024
BACKGROUND: Older adults (≥65 years) account for a disproportionately high proportion of hospitalization and in-hospital mortality, some of which may be avoidable. Although machine learning (ML) models have already been built and validated for predic...
Machine learning to understand risks for severe COVID-19 outcomes: a retrospective cohort study of immune-mediated inflammatory diseases, immunomodulatory medications, and comorbidities in a large US health-care system.
The Lancet. Digital health
May 1, 2024
BACKGROUND: In the context of immune-mediated inflammatory diseases (IMIDs), COVID-19 outcomes are incompletely understood and vary considerably depending on the patient population studied. We aimed to analyse severe COVID-19 outcomes and to investig...
Machine Learning-Based Prediction of Hospitalization During Chemoradiotherapy With Daily Step Counts.
JAMA oncology
May 1, 2024
IMPORTANCE: Toxic effects of concurrent chemoradiotherapy (CRT) can cause treatment interruptions and hospitalizations, reducing treatment efficacy and increasing health care costs. Physical activity monitoring may enable early identification of pati...
Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration.
JAMA internal medicine
May 1, 2024
IMPORTANCE: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioratio...
Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures.
JCO clinical cancer informatics
Apr 1, 2024
PURPOSE: Adverse effects of chemotherapy often require hospital admissions or treatment management. Identifying factors contributing to unplanned hospital utilization may improve health care quality and patients' well-being. This study aimed to asses...
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