AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

East Asian People

Showing 1 to 10 of 124 articles

Clear Filters

The relationship between mindfulness and second language resilience among Chinese English majors: the mediating role of academic hope.

BMC psychology
BACKGROUND: In light of the heightened expectations surrounding the development of foreign language professionals in the age of artificial intelligence and the pursuit of academic excellence in Asian culture, Chinese English majors are faced with tre...

Boi-Ogi-To, a Traditional Japanese Kampo Medicine, Promotes Cellular Excretion of Chloride and Water by Activating Volume-Sensitive Outwardly Rectifying Anion Channels.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
The Japanese Kampo medicine Boi-ogi-to (BOT) is known as an effective therapeutic agent for edema and nephrosis by promoting the excretion of excess body fluids. Despite its empirical effectiveness, scientific evidence supporting its effectiveness re...

Exploratory Analysis of Nationwide Japanese Patient Safety Reports on Suicide and Suicide Attempts Among Inpatients With Cancer Using Large Language Models.

Psycho-oncology
OBJECTIVE: Patients with cancer have a high risk of suicide. However, evidence-based preventive measures remain unclear. This study aimed to investigate suicide prevention strategies for hospitalized patients with cancer by analyzing nationwide patie...

Circulating fibroblast growth factor 21 is associated with blood pressure in the Chinese population: a community-based study.

Annals of medicine
BACKGROUND: Our research team previously found that fibroblast growth factor (FGF) 21, a circulating hormone, was significantly associated with atherosclerosis in human and animal models. The relationship between FGF21 and blood pressure (BP) is rare...

Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus.

Scientific reports
Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to deve...

Machine Learning Model for Predicting Coronary Heart Disease Risk: Development and Validation Using Insights From a Japanese Population-Based Study.

JMIR cardio
BACKGROUND: Coronary heart disease (CHD) is a major cause of morbidity and mortality worldwide. Identifying key risk factors is essential for effective risk assessment and prevention. A data-driven approach using machine learning (ML) offers advanced...

Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.

Frontiers in endocrinology
BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that typically requires a standardized oral glucose tolerance test (OGTT) for diagnosis. This study aims to predict glucose tolerance status in Chinese Ha...

Chinese generative AI models (DeepSeek and Qwen) rival ChatGPT-4 in ophthalmology queries with excellent performance in Arabic and English.

Narra J
The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of digital medical consultations, with patients turning to AI-driven tools for guidance. The emergence of Chinese-developed genAI models such as DeepSeek-R1 an...

A study on factors influencing digital sports participation among Chinese secondary school students based on explainable machine learning.

Scientific reports
This study utilized data from 4,925 Hong Kong students in the 2018 Programme for International Student Assessment (PISA) to investigate factors influencing secondary school students' use of digital devices for sports participation and their threshold...

End-to-end Chinese clinical event extraction based on large language model.

Scientific reports
Clinical event extraction is crucial for structuring medical data, supporting clinical decision-making, and enabling other intelligent healthcare services. Traditional approaches for clinical event extraction often use pipeline-based methods to ident...