AIMC Topic: Inpatients
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Technology Integration to Support Nurses in an "Inpatient Room of the Future": Qualitative Analysis.
Journal of medical Internet research
Jun 16, 2025
BACKGROUND: The design and integration of technology within inpatient hospital rooms has a critical role in supporting nursing workflows, enhancing provider experience, and improving patient care. As health care technology evolves, there is a need to...
Artificial intelligence-assisted diagnosis and prognostication in low ejection fraction using electrocardiograms in inpatient department: a pragmatic randomized controlled trial.
BMC medicine
Jun 9, 2025
BACKGROUND: Early diagnosis of low ejection fraction (EF) remains challenging despite being a treatable condition. This study aimed to evaluate the effectiveness of an electrocardiogram (ECG)-based artificial intelligence (AI)-assisted clinical decis...
Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.
PloS one
Apr 30, 2025
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.
Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches.
BMC endocrine disorders
Mar 27, 2025
BACKGROUND: Hyperglycemic crisis is one of the most common and severe complications of diabetes mellitus, associated with a high motarlity rate. Emergency admissions due to hyperglycemic crisis remain prevalent and challenging. This study aimed to de...
Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.
Surgery
Mar 23, 2025
BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic regression in forecasting discharge against medical advice occurrences needs to be evaluated.
Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).
BMC psychiatry
Mar 18, 2025
BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) shows significant challenges as traditional diagnostic methods fail to meet expectations due to patient hesitance and non-psychiatric h...
Fast screening of COVID-19 inpatient samples by integrating machine learning and label-free SERS methods.
Analytica chimica acta
Feb 25, 2025
BACKGROUND: Advances in bio-analyte detection demonstrate the need for innovation to overcome the limitations of traditional methods. Emerging viruses evolve into variants, driving the need for fast screening to minimize the time required for positiv...
Machine learning based on nutritional assessment to predict adverse events in older inpatients with possible sarcopenia.
Aging clinical and experimental research
Feb 22, 2025
BACKGROUND: The accuracy of current tools for predicting adverse events in older inpatients with possible sarcopenia is still insufficient to develop individualized nutrition-related management strategies. The objectives were to develop a machine lea...
Constructing a fall risk prediction model for hospitalized patients using machine learning.
BMC public health
Jan 20, 2025
STUDY OBJECTIVES: This study aimed to identify the risk factors associated with falls in hospitalized patients, develop a predictive risk model using machine learning algorithms, and evaluate the validity of the model's predictions.
Machine-learning-based cost prediction models for inpatients with mental disorders in China.
BMC psychiatry
Jan 9, 2025
BACKGROUND: Mental disorders are increasingly prevalent, leading to increased medical expenditures. To refine the reimbursement of medical costs for inpatients with mental disorders by health insurance, an accurate prediction model is essential. Per-...
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