Hospital-Based Medicine

Latest AI and machine learning research in hospital-based medicine for healthcare professionals.

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An ingestible self-propelling device for intestinal reanimation.

Postoperative ileus (POI) is the leading cause of prolonged hospital stay after abdominal surgery an...

The learning curve of robot-assisted laparoscopic pyeloplasty in children.

To explore the learning curve of robot-assisted laparoscopic pyeloplasty (RALP) in children. The cli...

Study of medium and long-term free flow capacity and queue discharge rates on roads.

With the rise in vehicle ownership, traffic congestion has emerged as a major barrier to urban progr...

Recommendations for using artificial intelligence in clinical flow cytometry.

Flow cytometry is a key clinical tool in the diagnosis of many hematologic malignancies and traditio...

Classification of Action Potentials With High Variability Using Convolutional Neural Network for Motor Unit Tracking.

The reliable classification of motor unit action potentials (MUAPs) provides the possibility of trac...

Effect of insurance status on perioperative outcomes after robotic pancreaticoduodenectomy: a propensity-score matched analysis.

The influence of Medicaid or being uninsured is prevailingly thought to negatively impact a patient'...

Outcomes of robot-assisted versus video-assisted mediastinal mass resection during the initial learning curve.

To compare the learning curve of mediastinal mass resection between robot-assisted surgery and thora...

Machine learning decision support model for discharge planning in stroke patients.

BACKGROUND/AIM: Efficient discharge for stroke patients is crucial but challenging. The study aimed ...

Predicting reoperation and readmission for head and neck free flap patients using machine learning.

BACKGROUND: To develop machine learning (ML) models predicting unplanned readmission and reoperation...

Overview and Clinical Applications of Artificial Intelligence and Machine Learning in Cardiac Anesthesiology.

Artificial intelligence- (AI) and machine learning (ML)-based applications are becoming increasingly...

Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

AIM: This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict...

The weight of BMI in impacting postoperative and oncologic outcomes in pancreaticoduodenectomy is attenuated by a robotic approach.

This study was undertaken to observe the effect of body mass index (BMI) on perioperative outcomes a...

Malnutrition risk assessment using a machine learning-based screening tool: A multicentre retrospective cohort.

BACKGROUND: Malnutrition is associated with increased morbidity, mortality, and healthcare costs. Ea...

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for tracking scientific progress and bridging the current chasm between a...

Acute Kidney Injury in Acute Myocardial Infarction and Its Outcome at 3 and 6 Months.

Epidemiological data on the prevalence of acute kidney injury (AKI) in acute coronary syndrome are s...

Minimally invasive sacrocolpopexy: efficiency of robotic assistance compared to standard laparoscopy.

Minimally invasive abdominal sacrocolpopexy (SC) is the treatment of choice for symptomatic, high-gr...

A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department.

This study addresses the challenges associated with emergency department (ED) overcrowding and empha...

Comparing the Quality of Domain-Specific Versus General Language Models for Artificial Intelligence-Generated Differential Diagnoses in PICU Patients.

OBJECTIVES: Generative language models (LMs) are being evaluated in a variety of tasks in healthcare...

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