AIMC Topic: Humans

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A Machine Learning-Based Clustering Analysis to Explore Bisphenol A and Phthalate Exposure from Medical Devices in Infants with Congenital Heart Defects.

Environmental health perspectives
BACKGROUND: Plastic-containing medical devices are commonly used in critical care units and other patient care settings. Patients are often exposed to xenobiotic agents that are leached out from plastic-containing medical devices, including bisphenol...

Evaluating the readability, quality, and reliability of responses generated by ChatGPT, Gemini, and Perplexity on the most commonly asked questions about Ankylosing spondylitis.

PloS one
Ankylosing spondylitis (AS), which usually occurs in the second and third decades of life, is associated with chronic pain, limitation of mobility, and severe decreases in quality of life. This study aimed to make a comparative evaluation in terms of...

Advancing breast cancer prediction: Comparative analysis of ML models and deep learning-based multi-model ensembles on original and synthetic datasets.

PloS one
Breast cancer is a significant global health concern with rising incidence and mortality rates. Current diagnostic methods face challenges, necessitating improved approaches. This study employs various machine learning (ML) algorithms, including KNN,...

Comprehensive framework for thyroid disorder diagnosis: Integrating advanced feature selection, genetic algorithms, and machine learning for enhanced accuracy and other performance matrices.

PloS one
Thyroid hormones control crucial physiological activities, such as metabolism, oxidative stress, erythropoiesis, thermoregulation, and organ development. Hormonal imbalances may cause serious conditions like cognitive impairment, depression, and nerv...

Machine learning driven dashboard for chronic myeloid leukemia prediction using protein sequences.

PloS one
The prevalence of Leukaemia, a malignant blood cancer that originates from hematopoietic progenitor cells, is increasing in Southeast Asia, with a worrisome fatality rate of 54%. Predicting outcomes in the early stages is vital for improving the chan...

Does the registration system reform reduce the finance sector's risk spillover effect in China's stock market-Causal inference based on dual machine learning.

PloS one
With growing uncertainty in global trade, improving access to domestic capital markets has become an important way to manage financial risk spillovers. This study examines how the registration system reform affects the finance sector's risk spillover...

Research on learning achievement classification based on machine learning.

PloS one
Academic achievement is an important index to measure the quality of education and students' learning outcomes. Reasonable and accurate prediction of academic achievement can help improve teachers' educational methods. And it also provides correspond...

Text speaks louder: Insights into personality from natural language processing.

PloS one
In recent years, advancements in natural language processing (NLP) have enabled new approaches to personality assessment. This article presents an interdisciplinary investigation that leverages explainable AI techniques, particularly Integrated Gradi...

A multicentric study examining a deep-learning-based computer model for classifying bipolar disorder using retinal vascular images.

Journal of affective disorders
OBJECTIVES: Due to easy accessibility, the retina is considered a window to the brain. Recent studies have reported retinal vascular abnormalities in bipolar disorder. Deep learning analysis, an advanced computational approach, has been implemented i...

Managers' perceptions and attitudes toward the use of artificial intelligence technology in selected hospital settings.

International journal of medical informatics
BACKGROUND: Over the past decade, artificial intelligence (AI) has transformed healthcare systems by improving cost control, clinical decision-making, and chronic disease management. This study assessed healthcare managers' perceptions of AI use in h...