[Establishment of comprehensive evaluation models of physical fitness of the elderly based on machine learning].

The present study aims to establish comprehensive evaluation models of physical fitness of the elderly based on machine learning, and provide an important basis to monitor the elderly's physique. Through stratified sampling, the elderly aged 60 years and above were selected from 10 communities in Nanchang City. The physical fitness of the elderly was measured by the comprehensive physical assessment scale based on our previous study.

[Development of comprehensive vitality scale for the elderly based on classical test theory and analytic hierarchy process].

The present study aims to construct an elderly vitality index evaluation system and develop a comprehensive vitality evaluation scale for the elderly to reasonably evaluate the vitality level of the elderly in China, so as to provide a reference for promoting the realization of "active aging" and "healthy aging". Literature research and in-depth interview were used to collect the senile vitality sensitive indexes. The indexes were screened and corrected by Delphi expert consultation method, item analysis method based on classical test theory, factor analysis method, and reliability and validity analysis method.

Global research trends of artificial intelligence applied in esophageal carcinoma: A bibliometric analysis (2000-2022) CiteSpace and VOSviewer.

Objective: Using visual bibliometric analysis, the application and development of artificial intelligence in clinical esophageal cancer are summarized, and the research progress, hotspots, and emerging trends of artificial intelligence are elucidated.

Methods: On April 7th, 2022, articles and reviews regarding the application of AI in esophageal cancer, published between 2000 and 2022 were chosen from the Web of Science Core Collection. To conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field, VOSviewer (version 1.