AIMC Topic: Adult

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Cancer care coordination determinants of depression in head and neck cancer survivors.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aims to explore the role of patient-reported cancer care coordination in explaining depression among head and neck (HNC) cancer survivors.

Factors influencing the adoption of generative artificial intelligence into classroom teaching by university teachers: An empirical study using SPSS PROCESS macros.

PloS one
With the development of science and technology, higher education faces the challenge of AIGC. As one of the central bodies of higher education, it is essential to understand whether teachers accept this new technology and what factors influence their...

Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models.

PloS one
BACKGROUND: Lymphoma is a severe condition with high mortality rates, often requiring ICU admission. Traditional risk stratification tools like SOFA and APACHE scores struggle to capture complex clinical interactions. Machine learning (ML) models off...

Metabolomics and nutrient intake reveal metabolite-nutrient interactions in metabolic syndrome: insights from the Korean Genome and Epidemiology Study.

Nutrition journal
BACKGROUND: Despite advances in metabolomics, the complex relationship between metabolites and nutrient intake in metabolic syndrome (MetS) remains poorly understood in the Korean population.

A machine learning approach to predict self-efficacy in breast cancer survivors.

BMC medical informatics and decision making
PURPOSE: To determine predictors of self-efficacy in breast cancer survivors and identify vulnerable groups.

Predictive value of anthropometric indices for incident of dyslipidemia: a large population-based study.

Population health metrics
INTRODUCTION: Dyslipidemia as a modifiable risk factor for chronic non-communicable diseases has become a worldwide concern. We aim to explore different anthropometric measures as predictors of dyslipidemia using various machine learning methods.

Real-world data of CanAssist Breast- first immunohistochemistry and AI-based prognostic test.

Scientific reports
CanAssist Breast (CAB), an immunohistochemistry (IHC) and artificial intelligence-based prognostic test, was developed on Hormone receptor-positive (HR +), HER2/neu-negative (HER2-) breast tumors from Indian patients and validated in retrospective gl...

Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations.

Scientific reports
Sepsis is a condition resulting from the uncontrolled immune response to infection, leading to widespread inflammatory damage and potentially fatal organ dysfunction. Currently, there is a lack of specific prevention and treatment strategies for seps...

Predicting cancer risk using machine learning on lifestyle and genetic data.

Scientific reports
Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. This study investigates the application of Machine Learning (ML) techniques to predict cancer...

The role of personality traits in predicting educational use of generative AI in higher education.

Scientific reports
Generative Artificial Intelligence (Gen-AI) systems offer significant opportunities for personalized learning in higher education. Studying the effects of personality traits on the use of Gen-AI is crucial for understanding the role of individual dif...