Prevention of medical errors

Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.

The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for clinical prevention and control. A total of 1949 patients with P.aeruginosa health care-associated infections (HAIs) were enrolled in this study. A to...

Formative evaluation of the acceptance of HIV prevention Artificial Intelligence chatbots by Black gay, bisexual, and other men who have sex with men in the Southern United States: Focus group study.

Gay, bisexual, and other men who have sex with men (MSM) account for 60% of new HIV infections among Black Americans in the Southern United States (U.S.). Despite recommendations for frequent HIV testing and daily pre-exposure prophylaxis (PrEP) uptake, there remains a gap in PrEP uptake among these Black MSM in the Southern U.S. Artificial Intelligence (AI) chatbots have the potential to boost us...

Educating Medical Students on Deaf-Hearing Interpreter Teams: A Virtual Patient Panel Experience.

Communication and cultural differences render d/Deaf patients vulnerable to poorer health outcomes when compared to their hearing peers. Interventions...

Ethical Considerations for Generative Artificial Intelligence in Plastic Surgery.

The integration of artificial intelligence (AI) into surgical care is rapidly transforming healthcare by enhancing efficiency, clinical decision-makin...

Embracing change in AAC technology: the keyboard to my success.

My name is Tim Jin, and I use an augmentative and alternative communication (AAC) device by typing with my toes. My communication journey has spanned ...

Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A Retrospective Registry-Based Study.

STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insight...

Prediction of Ligand-Receptor Interactions Based on CatBoost and Deep Forest and Their Application in Cell-Cell Communication Analysis.

Cell-to-cell communication (CCC) is prominent for cell growth and development as well as tissue and organ formation. CCC inference can help us to deep...

Single-tooth resolved, whole-mouth prediction of early childhood caries via spatiotemporal variations of plaque microbiota.

Early childhood caries (ECC) exhibits tooth specificity, highlighting the need for single-tooth-level prevention. We profiled 2,504 dental plaque micr...

Revolutionizing diabetes care: the role of artificial intelligence in prevention, diagnosis, and patient care.

UNLABELLED: Millions of people worldwide have diabetes, a disease that is becoming more common and has substantial socioeconomic costs. Artificial int...

Empowering Pharmacists in Type 2 Diabetes Care: Opportunities for Prevention, Counseling, and Therapeutic Optimization.

Diabetes is a growing chronic disease with complications that impose a significant burden on healthcare systems worldwide. Pharmacists are readily acc...

Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis.

OBJECTIVES: Decades of clinical and fundamental research advancements in oncology have led to significant breakthroughs such as early screening, targe...

Blood pressure monitoring is key in aortic dissection.

Blood pressure (BP) control is essential for both the prevention and long-term management of aortic dissection. While office BP monitoring remains the...

Machine Learning and Artificial Intelligence in Suicide Prevention: A Bibliometric Analysis of Emerging Trends and Implications for Nursing.

Nurses play a crucial role in suicide prevention, yet the integration of artificial intelligence and machine learning technologies into nursing practi...

The risk factors for relapse behavior in individuals with substance use disorders: An interpretable machine learning study.

BACKGROUND: Substance abuse has become a serious public health problem worldwide, and finding effective prevention and treatment strategies is undoubt...

Vessel-Like Microtunnels with Biomimetic Octopus Tentacles for Seizing and Detecting Exosomes to Diagnose Pancreatic Cancer.

Microchip-based exosome analysis has emerged as a promising approach for liquid biopsy in cancer diagnosis, treatment monitoring, and prognostic evalu...

Interpretable niche-based cell‒cell communication inference using multi-view graph neural networks.

Cell‒cell communication (CCC) is a fundamental biological process for the harmonious functioning of biological systems. Increasing evidence indicates ...

Burn disasters in North Carolina: An Analysis of Four Major Incidents with a Look to the Future.

This paper examines the medical response to four significant burn disasters in the North Carolina: the Pope Air Force Base disaster, the ConAgra/Garne...

Bi directional sparse attention recurrent autoencoder based intrusion detection for VANET security with tuna swarm optimization.

Vehicular Ad-hoc Networks (VANETs) have garnered a lot of consideration and research in last decades. By enhancing safety and comfort, VANETs are esse...

Deep ensemble framework with Bayesian optimization for multi-lesion recognition in capsule endoscopy images.

In order to address the challenges posed by the large number of images acquired during wireless capsule endoscopy examinations and fatigue-induced lea...

Dynamic event-triggered adaptive control for electro-hydraulic servomechanism.

This paper investigates the adaptive robust control of electro-hydraulic servomechanisms subject to restricted data communication, unmeasurable state ...