Hospitalists

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning.

Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spatial climate variability and land use/land cover (LULC) changes on surface water yield and availability in the Gilgel Gibe watershed, Ethiopia, from 1993 to 2023. Utilizin...

Predicting Mortality in Atrial Fibrillation Patients Treated with Direct Oral Anticoagulants: A Machine Learning Study Based on the MIMIC-IV Database.

Atrial fibrillation (AF) is a common arrhythmia linked to increased mortality and significant healthcare burden, especially in the elderly. Direct Oral Anticoagulants (DOACs) are crucial for stroke prevention in AF, offering benefits over traditional vitamin K antagonists. Despite scoring systems like HATCH and CHA2DS2-VASc, their predictive ability for mortality in AF patients is limited. This s...

Predictive machine learning model for 30-day hospital readmissions in a tertiary healthcare setting.

MOTIVATION: Hospital readmissions represent a major challenge for healthcare systems due to their impact on patient outcomes and associated costs. As ...

Nucleation and Growth Mechanisms of Micro/Nano Structural Manganese-Trimesic Acid Coordinations for Aqueous Zinc-Ion Batteries.

Nucleation and growth of metal-organic frameworks (MOFs) are critical for controlling their morphology, size, and performance. Guided by the crystal n...

Reply to: Optimizing external validation of deep neural networks for interictal discharge detection.

Optimizing external validation of deep neural networks for interictal discharge detection.

Association between fibrinogen levels and prognosis in critically bleeding patients: exploration of the optimal therapeutic threshold.

BACKGROUND: Severe bleeding is a leading cause of ICU admission and mortality. Fibrinogen plays a crucial role in prognosis, yet optimal thresholds an...

Performance of Machine Learning Models in Predicting 30-Day General Medicine Readmissions Compared to Traditional Approaches in Australian Hospital Setting.

: Hospital readmissions are a key quality metric impacting both patient outcomes and healthcare costs. Traditional logistic regression models, includi...

Using interpretable survival analysis to assess hospital length of stay.

Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decis...

Strategies to Reduce Hospital Length of Stay: Evidence and Challenges.

Hospital length of stay (HLOS) is a critical healthcare metric influencing patient outcomes, resource utilization, and healthcare costs. While reducin...

Applying Machine Learning to the ANZELA-QI Database to Predict Adverse Outcomes for Patients Undergoing Emergency Laparotomy.

BACKGROUND: Emergency laparotomy is associated with high rates of morbidity and mortality. Accurate, individualised risk prediction models can be used...

The "Outpatient Arthroplasty Risk Assessment" Score for Same Day Outpatient Primary Total Joint Arthroplasty: A Multicenter Study.

BACKGROUND: The Outpatient Arthroplasty Risk Assessment (OARA) Score was developed to risk-stratify patients for safe same-day discharge outpatient to...

Holistic characterization of water quality parameters to understand the ecological impacts of eutrophication.

The naturally oligotrophic waters of the Florida Keys, U.S.A., can be impacted by small increases in nutrients, which are reflected by increased phyto...

Propofol-associated Hypertriglyceridemia: Development and Multicenter Validation of a Machine-Learning-Based Prediction Tool.

To develop and validate an explainable machine learning (ML) tool to help clinicians predict the risk of propofol-associated hypertriglyceridemia in c...

High procalcitonin level is related to blood stream infections, gram-negative pathogens, and ICU admission in infections of adult febrile cancer patients.

BACKGROUND: Blood stream infection (BSI) represent a life-threatening condition. Thus, we aimed to investigate the role of procalcitonin (PCT) and C-r...

Impact of dielectric barrier discharge cold plasma on Dendrobium officinale polysaccharides: Physicochemical and functional properties.

Dendrobium officinale has garnered significant attention due to its notable bioactivity and health benefits. The polysaccharide extracted from Dendrob...

Assessing artificial intelligence-generated patient discharge information for the emergency department: a pilot study.

BACKGROUND: Effective patient discharge information (PDI) in emergency departments (EDs) is vital and often more crucial than the diagnosis itself. Pa...

Incremental capacity analysis of battery under dynamic load conditions.

The inconsistent charge and discharge patterns of electric vehicle batteries, coupled with their operation across varying voltage and current levels, ...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic. Accurate prediction of in-hospital mortality of p...

Machine Learning-Based Prediction of Unplanned Readmission Due to Major Adverse Cardiac Events Among Hospitalized Patients with Blood Cancers.

BackgroundHospitalized patients with blood cancer face an elevated risk for cardiovascular diseases caused by cardiotoxic cancer therapies, which can ...