AIMC Topic: Adult

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Association of the dietary index for gut microbiota with metabolic syndrome and its components combining interpretable machine learning algorithms.

Journal of health, population, and nutrition
BACKGROUND: Previous studies have emphasized the critical role of diet and gut microbiome in Metabolic syndrome (MetS). The dietary index for gut microbiota (DI-GM) represents a novel dietary index that effectively reflects the diversity of gut micro...

Functional archetypes in the human gut microbiome reveal metabolic diversity, stability, and influence disease-associated signatures.

Microbiome
BACKGROUND: Understanding the functional diversity of the gut microbiome is critical for elucidating its roles in human health and disease. While traditional approaches focus on taxonomic composition, functional configurations of the microbiome remai...

Serum lipid metabolic characteristics and potential biomarkers in first-episode schizophrenia.

BMC psychiatry
BACKGROUND: Lipids play a vital role in health and disease, but changes to their circulating levels and the link with schizophrenia remains poorly characterized. This study aimed to investigate the pathological lipid profiles in patients with first-e...

Artificial intelligence-based diagnosis of diabetic kidney disease using urinary VOC biosensor data.

BMC nephrology
BACKGROUND: Diabetic kidney disease (DKD) remains a leading cause of chronic kidney disease worldwide. However, current diagnostic methods rely on indirect biomarkers or invasive renal biopsy. This study aimed to evaluate the feasibility of urinary v...

Qualitative and quantitative assessment of accelerated liver diffusion-weighted imaging using deep-learning reconstruction in oncologic patients.

BMC medical imaging
BACKGROUND: Deep-learning (DL) reconstructions could improve image quality and reduce acquisition time in diffusion-weighted imaging (DWI). This study assessed, qualitatively and quantitatively, DL-DWI in liver metastasis of colorectal cancer patient...

A gamification training system designed according to a mental model structure: A case study of universal robots.

Scientific reports
As part of the industrial revolution, the collaborative robot (cobot) has become increasingly important in Industry 5.0. However, the most significant barrier for the industry to adopt the cobot is a lack of knowledge and skills. Therefore, e-learnin...

The global epidemiology, risk factors, and mortality prediction of nocardiosis: an easily missed opportunistic infection.

Scientific reports
This study was to comprehensively investigate the epidemiology of nocardiosis worldwide and develop an interpretable machine learning (ML) model to predict mortality in patients with nocardiosis. The PubMed and Web of Science databases were searched ...

Reconstructing music perception from brain activity using a prior guided diffusion model.

Scientific reports
Reconstructing music directly from brain activity provides insight into the neural representations underlying auditory processing and paves the way for future brain-computer interfaces. We introduce a fully data-driven pipeline that combines cross-su...

Towards decoding individual words from non-invasive brain recordings.

Nature communications
While deep learning has enabled the decoding of language from intracranial brain recordings, achieving this with non-invasive recordings remains an open challenge. We introduce a deep learning pipeline to decode individual words from electro- (EEG) a...

Temporal structure of natural language processing in the human brain corresponds to layered hierarchy of large language models.

Nature communications
Large Language Models (LLMs) offer a framework for understanding language processing in the human brain. Unlike traditional models, LLMs represent words and context through layered numerical embeddings. Here, we demonstrate that LLMs' layer hierarchy...