AIMC Topic: East Asian People

Clear Filters Showing 51 to 60 of 132 articles

Development and validation of a deep learning-based survival prediction model for pediatric glioma patients: A retrospective study using the SEER database and Chinese data.

Computers in biology and medicine
OBJECTIVE: Develop a time-dependent deep learning model to accurately predict the prognosis of pediatric glioma patients, which can assist clinicians in making precise treatment decisions and reducing patient risk.

Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study.

JMIR medical informatics
BACKGROUND: Natural language processing (NLP) techniques can be used to analyze large amounts of electronic health record texts, which encompasses various types of patient information such as quality of life, effectiveness of treatments, and adverse ...

Can AI-Generated Clinical Vignettes in Japanese Be Used Medically and Linguistically?

Journal of general internal medicine
BACKGROUND: Creating clinical vignettes requires considerable effort. Recent developments in generative artificial intelligence (AI) for natural language processing have been remarkable and may allow for the easy and immediate creation of diverse cli...

Machine learning-based model for worsening heart failure risk in Chinese chronic heart failure patients.

ESC heart failure
AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clini...

Individualized prediction of non-sentinel lymph node metastasis in Chinese breast cancer patients with ≥ 3 positive sentinel lymph nodes based on machine-learning algorithms.

BMC cancer
BACKGROUND: Axillary lymph node dissection (ALND) is a standard procedure for early-stage breast cancer (BC) patients with three or more positive sentinel lymph nodes (SLNs). However, ALND can lead to significant postoperative complications without a...

Grading facial aging: Comparing the clinical assessments made by three dermatologists with those obtained by an AI-based scoring system that analyses selfie pictures. A focus on Chinese subjects of both genders.

International journal of cosmetic science
OBJECTIVE: The objective of this study is to assess the correspondence, in live conditions, between clinical gradings of facial aging signs by three dermatologists and those afforded by an automatic AI-based algorithm that analyses smartphones' selfi...

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.

Thoracic cancer
BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical tre...

Trajectory on postpartum depression of Chinese women and the risk prediction models: A machine-learning based three-wave follow-up research.

Journal of affective disorders
BACKGROUND: Our study delves into postpartum depression (PPD) extending observation up to six months postpartum, addressing the gap in long-term follow-ups and uncover critical intervention points.

Deep learning and its associated factors among Chinese nursing undergraduates: A cross-sectional study.

Nurse education today
BACKGROUND: Adequate professional preparation of nursing undergraduates is conducive to developing health care careers. Deep learning is important for enhancing nursing competencies and the overall quality of students. However, limited research has b...

Educational Utility of Clinical Vignettes Generated in Japanese by ChatGPT-4: Mixed Methods Study.

JMIR medical education
BACKGROUND: Evaluating the accuracy and educational utility of artificial intelligence-generated medical cases, especially those produced by large language models such as ChatGPT-4 (developed by OpenAI), is crucial yet underexplored.