AI Medical Compendium Topic

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Hospitalization

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Enhancing Pressure Injury Surveillance Using Natural Language Processing.

Journal of patient safety
OBJECTIVE: This study assessed the feasibility of nursing handoff notes to identify underreported hospital-acquired pressure injury (HAPI) events.

Deep learning prediction of hospital readmissions for asthma and COPD.

Respiratory research
QUESTION: Severe asthma and COPD exacerbations requiring hospitalization are linked to increased disease morbidity and healthcare costs. We sought to identify Electronic Health Record (EHR) features of severe asthma and COPD exacerbations and evaluat...

Machine learning-driven development of a disease risk score for COVID-19 hospitalization and mortality: a Swedish and Norwegian register-based study.

Frontiers in public health
AIMS: To develop a disease risk score for COVID-19-related hospitalization and mortality in Sweden and externally validate it in Norway.

Machine learning models for early prediction of mortality risk in patients with burns: A single center experience.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
Mortality rate is considered as the most important outcome measure for assessing the severity of burn injury. A scale or model that accurately predicts burn mortality can be useful to determine the clinical course of burn injuries, discuss treatment ...

CT-derived pectoralis composition and incident pneumonia hospitalization using fully automated deep-learning algorithm: multi-ethnic study of atherosclerosis.

European radiology
BACKGROUND: Pneumonia-related hospitalization may be associated with advanced skeletal muscle loss due to aging (i.e., sarcopenia) or chronic illnesses (i.e., cachexia). Early detection of muscle loss may now be feasible using deep-learning algorithm...

How AI is advancing asthma management? Insights into economic and clinical aspects.

Journal of medical economics
Asthma, an increasingly prevalent chronic respiratory condition, incurs significant economic costs worldwide. Artificial Intelligence (AI), particularly Machine Learning (ML), has been widely recognized as transformative when applied to asthma care. ...

Forecasting the Acute Heart Failure Admissions: Development of Deep Learning Prediction Model Incorporating the Climate Information.

Journal of cardiac failure
BACKGROUND: Climate is known to influence the incidence of cardiovascular events. However, their prediction with traditional statistical models remains imprecise.

Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data.

Birth defects research
BACKGROUND: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) collects data abstracted from medical records and birth defects registries on pregnant people and their infants to understand outcomes associated with ...

Prediction of hospitalization and waiting time within 24 hours of emergency department patients with unstructured text data.

Health care management science
Overcrowding of emergency departments is a global concern, leading to numerous negative consequences. This study aimed to develop a useful and inexpensive tool derived from electronic medical records that supports clinical decision-making and can be ...

Machine learning in clinical practice: Evaluation of an artificial intelligence tool after implementation.

Emergency medicine Australasia : EMA
OBJECTIVE: Artificial intelligence (AI) has gradually found its way into healthcare, and its future integration into clinical practice is inevitable. In the present study, we evaluate the accuracy of a novel AI algorithm designed to predict admission...