Yihong Chen
Biographic Data
| ID | 8301607 |
|---|---|
| NAME | Yihong Chen |
| GIVEN NAMES | Yihong |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN Y |
| AFFILIATIONS | University of Macau |
| ORCID | 0000-0001-5176-4551 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A feasibility and preliminary effectiveness study of a tiered gynecological laparoscopic training curriculum in southwestern China
BACKGROUND: Essential yet deficient gynecological laparoscopy training in China demands urgent structured solutions. This study aimed to develop and preliminarily evaluate a specialized laparoscopic surgical training curriculum for enhancing surgical skills among gynecologists. METHODS: Our laparoscopic training program ran from September 2022 to December 2025 and comprised three phases. Phase I developed a laparoscopic skills curriculum through …
Behavioural theories in smart tourism
Although behavioural theories are commonly referenced in smart tourism research, a comprehensive examination of these theoretical constructs within the smart tourism context remains scarce. This study reveals the intricate application contexts and mechanisms underpinning behavioural theories in smart tourism through a content analysis of 200 selected interdisciplinary publications. This research begins with foundational concepts and application c…
Forecasting visitor volume with spatiotemporal models of big data
Accurate visitor volume forecasting is essential for the effective management of tourism attractions, particularly during peak periods. Although previous studies have recognized the importance of incorporating spatial relationships into forecasting processes, the spatiotemporal associations between big data–based exogenous variables and tourism demand remain unexplored. This study tests six spatiotemporal models that integrate the spatiotemporal …
Association of exposure to PM2.5-bound metals with premature rupture of membranes: A prospective cohort study
Background Exposure to PM 2.5 has been linked to premature rupture of membranes (PROM). However, research on the effects of PM 2.5 -bound metals on the PROM is limited. Methods Here, we investigated this relationship using data from 6090 pregnant women, estimating exposure to 11 PM 2.5 -bound metals throughout pregnancy. Cox models assessed associations between individual metals and PROM, while grouped weighted quantile sum regression (GWQS), qua…
The impact of visual, auditory, textual stimuli on crowdfunding: Evidence from tourism projects
Discover the secrets to crowdfunding triumph. In start-up tourism enterprises, mastering the art of captivating and converting users into sponsors through multimodal stimuli is paramount. Researchers used deep learning to deeply mine the text, images and video promotional content of 3,659 travel crowdfunding projects and nine classifiers to predict crowdfunding project success dynamically. We unearthed fascinating insights: Images spark attention…
Tourism demand forecasting: A novel multi-channel imaging model
Purpose This study aims to introduce an innovative multi-channel imaging technique aimed at mitigating deep learning overfitting and facilitating the automatic extraction of features from limited 1D data. Design/methodology/approach The proposed framework consists of five key component: dimensionality reduction, sequence image generation, image stitching, feature extraction and model training. It converts 1D multi-temporal data into multiple 2D i…
Disease burden and attributable risk factors of lip and oral cavity cancer in China from 1990 to 2021 and its prediction to 2031
Aims: This study addresses the essential need for updated information on the burden of lip and oral cavity cancer (LOC) in China for informed healthcare planning. We aim to estimate the temporal trends and the attributable burdens of selected risk factors of LOC in China (1990-2021), and to predict the possible trends (2022-2031). Subject and methods: Analysis was conducted using data from the Global Burden of Disease study (GBD) 2021, encompassi…
Identifying the role of media discourse in tourism demand forecasting
High-frequency and timely tourism demand forecasting of fine-grained attractions is an effective tool that helps tourism stakeholders make decisions and formulate strategies. However, there are limitations due to the external sensitivity of tourism demand. This research integrated news coverage with other psychosocial variables to comprehensively explore the impact of social unrest on tourism demand. Topic modelling was applied to identify touris…
No prominent works on this page.
Disease burden and attributable risk factors of lip and oral cavity cancer in China from 1990 to 2021 and its prediction to 2031
Aims: This study addresses the essential need for updated information on the burden of lip and oral cavity cancer (LOC) in China for informed healthcare planning. We aim to estimate the temporal trends and the attributable burdens of selected risk factors of LOC in China (1990-2021), and to predict the possible trends (2022-2031). Subject and methods: Analysis was conducted using data from the Global Burden of Disease study (GBD) 2021, encompassi…
Identifying the role of media discourse in tourism demand forecasting
High-frequency and timely tourism demand forecasting of fine-grained attractions is an effective tool that helps tourism stakeholders make decisions and formulate strategies. However, there are limitations due to the external sensitivity of tourism demand. This research integrated news coverage with other psychosocial variables to comprehensively explore the impact of social unrest on tourism demand. Topic modelling was applied to identify touris…
Association of exposure to PM2.5-bound metals with premature rupture of membranes: A prospective cohort study
Background Exposure to PM 2.5 has been linked to premature rupture of membranes (PROM). However, research on the effects of PM 2.5 -bound metals on the PROM is limited. Methods Here, we investigated this relationship using data from 6090 pregnant women, estimating exposure to 11 PM 2.5 -bound metals throughout pregnancy. Cox models assessed associations between individual metals and PROM, while grouped weighted quantile sum regression (GWQS), qua…
The impact of visual, auditory, textual stimuli on crowdfunding: Evidence from tourism projects
Discover the secrets to crowdfunding triumph. In start-up tourism enterprises, mastering the art of captivating and converting users into sponsors through multimodal stimuli is paramount. Researchers used deep learning to deeply mine the text, images and video promotional content of 3,659 travel crowdfunding projects and nine classifiers to predict crowdfunding project success dynamically. We unearthed fascinating insights: Images spark attention…
Tourism demand forecasting: A novel multi-channel imaging model
Purpose This study aims to introduce an innovative multi-channel imaging technique aimed at mitigating deep learning overfitting and facilitating the automatic extraction of features from limited 1D data. Design/methodology/approach The proposed framework consists of five key component: dimensionality reduction, sequence image generation, image stitching, feature extraction and model training. It converts 1D multi-temporal data into multiple 2D i…
A feasibility and preliminary effectiveness study of a tiered gynecological laparoscopic training curriculum in southwestern China
BACKGROUND: Essential yet deficient gynecological laparoscopy training in China demands urgent structured solutions. This study aimed to develop and preliminarily evaluate a specialized laparoscopic surgical training curriculum for enhancing surgical skills among gynecologists. METHODS: Our laparoscopic training program ran from September 2022 to December 2025 and comprised three phases. Phase I developed a laparoscopic skills curriculum through …
Behavioural theories in smart tourism
Although behavioural theories are commonly referenced in smart tourism research, a comprehensive examination of these theoretical constructs within the smart tourism context remains scarce. This study reveals the intricate application contexts and mechanisms underpinning behavioural theories in smart tourism through a content analysis of 200 selected interdisciplinary publications. This research begins with foundational concepts and application c…
Forecasting visitor volume with spatiotemporal models of big data
Accurate visitor volume forecasting is essential for the effective management of tourism attractions, particularly during peak periods. Although previous studies have recognized the importance of incorporating spatial relationships into forecasting processes, the spatiotemporal associations between big data–based exogenous variables and tourism demand remain unexplored. This study tests six spatiotemporal models that integrate the spatiotemporal …
Tourism (5 works) · Digital Marketing and Social Media (4 works) · Computer Science (3 works) · Demand forecasting (3 works) · Diverse Aspects of Tourism Research (3 works) · Political science (3 works) · Business (2 works) · China (2 works) · Geography (2 works) · Internal Medicine (2 works)