AIMC Topic: Hospitalization

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Machine Learning to Differentiate Risk of Suicide Attempt and Self-harm After General Medical Hospitalization of Women With Mental Illness.

Medical care Feb 1, 2021
BACKGROUND: Suicide prevention is a public health priority, but risk factors for suicide after medical hospitalization remain understudied. This problem is critical for women, for whom suicide rates in the United States are disproportionately increas...
Risk Factors Hospitalization Aged Young Adult Retrospective Studies Electronic Health Records Female Reproducibility of Results Cohort Studies Supervised Machine Learning Patient Readmission Self-Injurious Behavior Women Adult Sensitivity and Specificity Middle Aged Suicide, Attempted Humans Algorithms Mental Disorders
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Early prediction of mortality risk among patients with severe COVID-19, using machine learning.

International journal of epidemiology Jan 23, 2021
BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection ...
Risk Assessment Hospitals Case-Control Studies ROC Curve Aged Sensitivity and Specificity Male Middle Aged Patient Admission Humans Machine Learning COVID-19 Female SARS-CoV-2 Hospitalization
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Construction of a Risk Prediction Model for Hospital-Acquired Pulmonary Embolism in Hospitalized Patients.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis Jan 1, 2021
The purpose of this study is to establish a novel pulmonary embolism (PE) risk prediction model based on machine learning (ML) methods and to evaluate the predictive performance of the model and the contribution of variables to the predictive perform...
Humans Machine Learning Prognosis Retrospective Studies Female Male Hospitalization Pulmonary Embolism Aged Cross Infection
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Artificial Intelligence in Acute Kidney Injury: From Static to Dynamic Models.

Advances in chronic kidney disease Jan 1, 2021
Artificial intelligence (AI) is the development of computer systems that normally require human intelligence. In the field of acute kidney injury (AKI) AI has led to an evolution of risk prediction models. In the past, static prediction models were d...
Artificial Intelligence Acute Kidney Injury Electronic Health Records Hospitalization Humans
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A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients.

Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis Jan 1, 2021
Deep venous thrombosis (DVT) is associated with significant morbidity, mortality, and increased healthcare costs. Standard scoring systems for DVT risk stratification often provide insufficient stratification of hospitalized patients and are unable t...
Risk Assessment Adolescent Venous Thrombosis Humans Machine Learning Risk Factors Hospitalization Adult Aged Male Young Adult Middle Aged
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Design of 1-year mortality forecast at hospital admission: A machine learning approach.

Health informatics journal Jan 1, 2021
Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life (QoL) for the last stage of life. They are currently based on clinical evaluation of the risk of 1-y...
Hospitals Hospital Mortality Machine Learning Retrospective Studies Hospitalization Quality of Life Humans
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Phenotypic clustering of heart failure with preserved ejection fraction reveals different rates of hospitalization.

Journal of cardiovascular medicine (Hagerstown, Md.) Jan 1, 2021
AIMS: Approximately 50% of patients with heart failure have preserved (≥50%) ejection fraction (HFpEF). Improved understanding of the phenotypic heterogeneity of HFpEF might facilitate development of targeted therapies and interventions.
Retrospective Studies Female Hospitalization Aged Aged, 80 and over Humans Databases, Factual Prognosis Age Factors Cluster Analysis Natural Language Processing Heart Failure Prevalence Data Mining Comorbidity Administrative Claims, Healthcare Male Time Factors Ventricular Function, Left United States Stroke Volume Middle Aged
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Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission.

Annals of surgery Dec 1, 2020
OBJECTIVE: To compare the performance of machine learning models against the traditionally derived Combined Assessment of Risk Encountered in Surgery (CARES) model and the American Society of Anaesthesiologists-Physical Status (ASA-PS) in the predict...
Preoperative Period Middle Aged Risk Assessment Postoperative Complications Time Factors Hospitalization Machine Learning Aged Prognosis Adult Retrospective Studies Male Intensive Care Units Female Humans
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The Development and Validation of a Machine Learning Model to Predict Bacteremia and Fungemia in Hospitalized Patients Using Electronic Health Record Data.

Critical care medicine Nov 1, 2020
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...
Aged Male Middle Aged Bacteremia Humans Female Blood Culture Machine Learning Reproducibility of Results Models, Statistical Retrospective Studies Risk Factors Fungemia Electronic Health Records Hospitalization
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Machine intelligence for early targeted precision management and response to outbreaks of respiratory infections.

The American journal of managed care Oct 1, 2020
OBJECTIVES: To evaluate the utility of machine learning (ML) for the management of Medicare beneficiaries at risk of severe respiratory infections in community and postacute settings by (1) identifying individuals in a community setting at risk of in...
Patient Discharge Hospitalization Humans Medicare Aged Respiratory Tract Infections Artificial Intelligence Disease Outbreaks Skilled Nursing Facilities Precision Medicine United States Retrospective Studies
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