AIMC Topic: Humans

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Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.

Journal of molecular neuroscience : MN
Ischemic stroke (IS) constitutes a severe neurological disorder with restricted treatment alternatives. Recent investigations have disclosed that glycosylation is closely associated with the occurrence and outcome of IS. Nevertheless, data on the tra...

From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.

Neurosurgical review
Gliomas are the most common primary tumors of the central nervous system, and advances in genetics and molecular medicine have significantly transformed their classification and treatment. This study aims to predict the IDH1 genotype in gliomas using...

A practical approach for colorectal cancer diagnosis based on machine learning.

PloS one
In this paper, we present the results of applying machine learning models to build a Colorectal Cancer Diagnosis system. The methodology encompasses six key steps: collecting raw data from Electronic Medical Records (EMRs), revising feature attribute...

NAH-GNN: A graph-based framework for multi-behavior and high-hop interaction recommendation.

PloS one
With the growing demand for personalized marketing, recommender systems have become essential tools to help users quickly discover products or content that match their interests. However, traditional recommendation methods face significant limitation...

Development and precision evaluation of a robotic system for oral implant surgery using personalized digital guides and optical spatial positioning technology.

PloS one
Oral implant surgery demands a high level of precision and expertise, making the integration of robotic assistance an optimal solution. This study introduces an innovative dental implant robotic system designed to enhance accuracy during cavity prepa...

Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk.

PloS one
In fast-paced urban environments, Citywalk has emerged as a key leisure activity for urban residents to alleviate stress and enhance emotional well-being. From the perspective of virtual-physical interaction, this study integrates social media data w...

Using large language models to learn from recent climate change discourse in public health.

PloS one
BACKGROUND: Public health has increasingly recognized the links between climate change and health, emphasizing the need to address related inequities. This is reflected in work led by the Intergovernmental Panel on Climate Change, the UN Framework Co...

Urban walkability through different lenses: A comparative study of GPT-4o and human perceptions.

PloS one
Urban environments significantly shape our well-being, behavior, and overall quality of life. Assessing urban environments, particularly walkability, has traditionally relied on computer vision and machine learning algorithms. However, these approach...

Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Exploring the pathogenic mechanisms of brain disorders within population is an important research in the field of neuroscience. Existing methods either combine clinical information to assist analysis or use data augmentation for sample expansion, ign...