AIMC Topic: Adult

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An explainable predictive machine learning model of gangrenous cholecystitis based on clinical data: a retrospective single center study.

World journal of emergency surgery : WJES
BACKGROUND: Gangrenous cholecystitis (GC) is a serious clinical condition associated with high morbidity and mortality rates. Machine learning (ML) has significant potential in addressing the diverse characteristics of real data. We aim to develop an...

Anti-ceramide antibody and sphingosine-1-phosphate as potential biomarkers of unresectable non-small cell lung cancer.

Pathology oncology research : POR
OBJECTIVES: Spingosine-1-phosphate (S1P) and ceramides are bioactive sphingolipids that influence cancer cell fate. Anti-ceramide antibodies might inhibit the effects of ceramide. The aim of this study was to assess the potential role of circulating ...

Assessing fecal contamination from human and environmental sources using as an indicator in rural eastern Ethiopian households-a cross-sectional study from the EXCAM project.

Frontiers in public health
INTRODUCTION: Enteric pathogens are a leading causes of diarrheal deaths in low-and middle-income countries. The Exposure Assessment of Infections in Rural Ethiopia (EXCAM) project, aims to identify potential sources of bacteria in the genus and, m...

Development and validation of a support vector machine-based nomogram for diagnosis of obstetric antiphospholipid syndrome.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Antiphospholipid Syndrome (APS) is a systemic autoimmune disorder characterized by arterial or venous thrombosis and/or pregnancy complications. This study aims to develop a diagnostic model for Obstetric APS (OAPS) using the Support Vect...

High performance COVID-19 screening using machine learning.

La Tunisie medicale
Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an international concern of public health emergency in the early 2020, several strategies have been initiated in many countries to prevent healthcare ser...

A Deep Learning-Based Framework Oriented to Pathological Gait Recognition with Inertial Sensors.

Sensors (Basel, Switzerland)
Abnormal locomotor patterns may occur in case of either motor damages or neurological conditions, thus potentially jeopardizing an individual's safety. Pathological gait recognition (PGR) is a research field that aims to discriminate among different ...

Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study.

BMC emergency medicine
BACKGROUND: In Sweden with about 10 million inhabitants, there are about one million primary ambulance missions every year. Among them, around 10% are assessed by Emergency Medical Service (EMS) clinicians with the primary symptom of dyspnoea. The ri...

Examining sustainable hospitality practices and employee turnover in Pakistan: The interplay of robotics awareness, mutual trust, and technical skills development in the age of artificial intelligence.

Journal of environmental management
Integrating robots and artificial intelligence (AI) into workplaces is becoming increasingly prevalent across various sectors, including hospitality. This trend has raised concerns regarding employee anxiety and the potential for higher turnover inte...

Facilitators and Barriers of Large Language Model Adoption Among Nursing Students: A Qualitative Descriptive Study.

Journal of advanced nursing
AIM: To explore nursing students' perceptions and experiences of using large language models and identify the facilitators and barriers by applying the Theory of Planned Behaviour.