Hospital-Based Medicine

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

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 options and rehabilitation with patients and their families, and evaluate novel, innovative interventions for the injuries. This study aimed to use ma...

Retracted: Diagnostic Value of SonoVue Contrast-Enhanced Ultrasonography in Nipple Discharge Based on Artificial Intelligence.

[This retracts the article DOI: 10.1155/2021/2961697.].

Machine Learning Web Application for Predicting Functional Outcomes in Patients With Traumatic Spinal Cord Injury Following Inpatient Rehabilitation.

Accurately predicting functional outcomes in patients with spinal cord injury (SCI) helps clinicians set realistic functional recovery goals and impro...

Predicting the Climate Impact of Healthcare Facilities Using Gradient Boosting Machines.

Health care accounts for 9-10% of greenhouse gas (GHG) emissions in the United States. Strategies for monitoring these emissions at the hospital level...

Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study.

: While Enterobacteriaceae bacteria are commonly found in the healthy human gut, their colonization of other body parts can potentially evolve into se...

Applying artificial intelligence to predict falls for inpatient.

OBJECTIVE: Falls are adverse events which commonly occur in hospitalized patients. Inpatient falls may cause bruises or contusions and even a fracture...

Robotic-assisted laparoscopic colpectomy combined with a hysterectomy and bilateral salpingo-oophorectomy versus a vaginal colpectomy in trans masculine individuals.

Colpectomy entails the surgical removal of the vaginal epithelium. It may be performed in trans-masculine individuals as gender-affirming surgery. Va...

Prediction of therapeutic intensity level from automatic multiclass segmentation of traumatic brain injury lesions on CT-scans.

The prediction of the therapeutic intensity level (TIL) for severe traumatic brain injury (TBI) patients at the early phase of intensive care unit (IC...

Robotic retroperitoneal lymph node dissection for paratesticular rhabdomyosarcoma in adolescents: a case series.

Robotic assisted (RA) retroperitoneal lymph node dissection (RPLND) has grown in popularity as it offers decreased morbidity and faster recovery compa...

ChatGPT and Artificial Intelligence in Hospital Level Research: Potential, Precautions, and Prospects.

Rapid advancements in artificial intelligence (AI) have revolutionized numerous sectors, including medical research. Among the various AI tools, OpenA...

Predicting stroke outcome: A case for multimodal deep learning methods with tabular and CT Perfusion data.

MOTIVATION: Acute ischemic stroke is one of the leading causes of morbidity and disability worldwide, often followed by a long rehabilitation period. ...

Current trends and future perspectives of stroke management through integrating health care team and nanodrug delivery strategy.

Stroke is accounted as the second-most mortality and adult disability factor in worldwide, while causes the bleeding promptly and lifetime consequence...

Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.

Delirium is a syndrome of acute brain failure which is prevalent amongst older adults in the Intensive Care Unit (ICU). Incidence of delirium can sign...

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine ...

Leveraging three-tier deep learning model for environmental cleaner plants production.

The world's population is expected to exceed 9 billion people by 2050, necessitating a 70% increase in agricultural output and food production to meet...

Predicting long-term neurocognitive outcome after pediatric intensive care unit admission for bronchiolitis-preliminary exploration of the potential of machine learning.

PURPOSE: For successful prevention and intervention, it is important to unravel the complex constellation of factors that affect neurocognitive functi...

The 2022 Banff Meeting Lung Report.

The Lung Session of the 2022 16th Banff Foundation for Allograft Pathology Conference-held in Banff, Alberta-focused on non-rejection lung allograft p...

India ink to 3D imaging: The legacy of Dr. Deepak "Dee" N. Pandya and his influence on generations of neuroanatomists.

Dr. Deepak "Dee" Pandya spent his career as an internal medicine physician as well as in his respective laboratories at the Bedford, Massachusetts Vet...

Assessing optimal methods for transferring machine learning models to low-volume and imbalanced clinical datasets: experiences from predicting outcomes of Danish trauma patients.

INTRODUCTION: Accurately predicting patient outcomes is crucial for improving healthcare delivery, but large-scale risk prediction models are often de...

Artificial Intelligence and Postoperative Monitoring in Plastic Surgery.

Technological innovation has fueled an evolving landscape in plastic surgery. Recently, artificial intelligence (AI) has demonstrated tremendous poten...