Hospitalists

Standard-of-care vs. machine learning-recommended discharge destinations for geriatric surgical inpatients: algorithm development and internal validation.

PURPOSE: Older adults undergoing surgery are at high risk for adverse outcomes due to age-related vulnerabilities. Comprehensive geriatric assessment (CGA) can improve discharge planning but is often limited by resource constraints. We evaluated whether machine learning (ML) can support individualized discharge destination recommendations for geriatric surgical inpatients. METHODS: We developed an...

Impact of a medication history software on a pharmacy-driven admission medication history and reconciliation program.

PURPOSE: Medication errors frequently occur during transitional periods between outpatient and inpatient care. This study aims to evaluate the impact of an outpatient-interfacing medication history software on medication history capture rates in a pharmacy-driven admission medication history and reconciliation program utilizing a hybrid pharmacy technician staffing model. METHODS: This retrospecti...

Robot-assisted gait training using a robotic exoskeleton during inpatient rehabilitation in acute Guillain-Barré Syndrome.

A woman in her early 60s with acute Guillain-Barré syndrome (GBS) developed rapidly progressive tetraparesis and respiratory failure requiring non-inv...

Development and external validation of a machine learning model for predicting tigecycline-associated drug-induced liver injury.

Tigecycline (TGC) is widely used to treat severe multidrug-resistant infections but can cause drug-induced liver injury. Existing prediction studies f...

Socioeconomic drivers of riverine biochemical oxygen demand: Insights from interpretable machine learning.

Biochemical oxygen demand (BOD5) is a comprehensive indicator for assessing organic pollution and water quality in rivers. Socioeconomic factors, such...

Strategies of Designing High-Efficiency Electrolyte Additives for Aqueous Magnesium Batteries: A Review.

With the development of next-generation energy storage systems focusing on green, safe, and sustainable devices, aqueous magnesium (Mg)-air batteries ...

Beyond Thresholds: Can Machine Learning Improve Trauma Field Triage?

BackgroundAccurate triage of trauma patients by Emergency Medical Services (EMS) is essential for optimal outcomes and resource allocation. The 2021 N...

Predicting KRT or Death in Critically Ill Patients with Rhabdomyolysis Using Machine Learning: A Multicenter Study.

BACKGROUND: Rhabdomyolysis is associated with outcomes ranging from muscle injury to AKI, KRT, and death. Early identification of patients at highest ...

Early prediction of anastomotic leakage within 24 h after minimally invasive colorectal cancer surgery using postoperative inflammatory markers: development and temporal validation of a machine learning model.

PURPOSE: Early identification of anastomotic leakage (AL) is critical for safe discharge within enhanced recovery pathways. This study developed and p...

Machine learning-optimized discharge timing in typhoid care: Implications for clinical outcomes, cost efficiency, and health system performance.

OBJECTIVE: To develop and validate a machine learning model identifying typhoid fever patients at risk of unnecessarily prolonged hospitalization, and...

Cardiac energetics and ventriculo-arterial interaction-based phenotyping in heart failure: a machine learning analysis.

Left-ventricular cardiac power output (CPO), stroke-work index (LVSWI), and ventriculo-arterial coupling (VAC) capture cardiac energetics and ventricu...

Generating Patient Documents from Electronic Health Records Using Generative Artificial Intelligence: A Feasibility Study in a Japanese Cancer Center.

OBJECTIVE: Clinical documentation consumes substantial clinician time, potentially detracting from patient care. Generative artificial intelligence (A...

[Overview and conclusions of the STROKE data platform of the National Laboratory for Translational Neuroscience and the associated clinical studies].

Acute ischemic and hemorrhagic stroke are among the leading causes of mortality and long-term disability worldwide. In addition to the results of rand...

Stage-specific predictors of exercise adherence after percutaneous coronary intervention: a prospective multicenter study.

BACKGROUND: The efficacy of exercise after Percutaneous Coronary Intervention (PCI) is compromised by poor long-term adherence. Although multiple infl...

Predicting severe COVID-19 in elderly patients using routine laboratory indicators: Diagnostic accuracy of machine learning models.

To enable early warning of severe 2019 coronavirus disease in elderly patients, this study collected routine laboratory indicators and clinical parame...

Machine-learning-guided control of a pulsed cold atmospheric plasma jet reveals a voltage-dependent discharge transition relevant to diabetic wound healing.

Cold atmospheric plasma (CAP) technology is promising for biomedical treatment, but its translation is limited by the difficulty of identifying operat...

Prospective Validation of Multi-week Inpatient Census Forecasting for Pediatric HSCT and Cellular Therapy.

BACKGROUND: Accurate inpatient census forecasting is important for cell therapy and blood and marrow transplantation (BMT) programs because bed capaci...

Earlier medically ready for discharge date entry associated with lower unnecessary bed days.

BACKGROUND: Discharge planning plays a critical role in managing patient hospital length of stay. We report on the implementation of a program in a la...

Effectiveness of an AI-augmented teacher feedback model in improving medical students' clinical documentation skills: a retrospective cohort study.

BACKGROUND: Clinical documentation is central to evaluating medical students' clinical competence. However, traditional teacher feedback is often inef...

Recent Advances in AI for Automated ICD Coding: A Systematic Literature Review.

International Classification of Diseases (ICD) codes enable correct billing, insurance reimbursement, and healthcare analytics. However, manual coding...