AIMC Topic: China

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Predicting functional outcome in ischemic stroke patients using genetic, environmental, and clinical factors: a machine learning analysis of population-based prospective cohort study.

Briefings in bioinformatics
Ischemic stroke (IS) is a leading cause of adult disability that can severely compromise the quality of life for patients. Accurately predicting the IS functional outcome is crucial for precise risk stratification and effective therapeutic interventi...

[Digital Intelligence Drives the High-Quality Development of the Healthcare Service System: Development Mechanisms and Implementation Pathway].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
The rapid development of digital intelligence technologies is providing a powerful boost to the high-quality development of the healthcare system. Considering the current state of our healthcare services and guided by General Secretary Xi Jinping's i...

[Progress in application of machine learning in epidemiology].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Population based health data collection and analysis are important in epidemiological research. In recent years, with the rapid development of big data, Internet and cloud computing, artificial intelligence has gradually attracted attention of epidem...

An artificial intelligence powered study of enlarged facial pore prevalence on one million Chinese from different age groups and its correlation with environmental factors.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Enlarged pores are amidst one of the top cosmetic concerns, especially among Chinese. Many small-group studies have been conducted in understanding their prevalence and beauty relevance. Nonetheless, population-level investigations are st...

Large language models leverage external knowledge to extend clinical insight beyond language boundaries.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Large Language Models (LLMs) such as ChatGPT and Med-PaLM have excelled in various medical question-answering tasks. However, these English-centric models encounter challenges in non-English clinical settings, primarily due to limited cli...

Multimodal ischemic stroke recurrence prediction model based on the capsule neural network and support vector machine.

Medicine
Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed based on single-modal biochemical tests, and imaging data have been used to predict stroke recurrence. However, the prediction accuracy of these models ...

[Soil Cadmium Prediction and Health Risk Assessment of an Oasis on the Eastern Edge of the Tarim Basin Based on Feature Optimization and Machine Learning].

Huan jing ke xue= Huanjing kexue
Soil heavy metal pollution poses a serious threat to food security, human health, and soil ecosystems. Based on 644 soil samples collected from a typical oasis located at the eastern margin of the Tarim Basin, a series of models, namely, multiple lin...

Machine Learning Models for Predicting Cycloplegic Refractive Error and Myopia Status Based on Non-Cycloplegic Data in Chinese Students.

Translational vision science & technology
PURPOSE: To develop and validate machine learning (ML) models for predicting cycloplegic refractive error and myopia status using noncycloplegic refractive error and biometric data.

Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.

Clinical cardiology
BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disea...