Tingting Fan
Biographic Data
| ID | 4059440 |
|---|---|
| NAME | Tingting Fan |
| GIVEN NAMES | Tingting |
| FAMILY NAME | Fan |
| SIGNATURE | FAN T |
| AFFILIATIONS | Nanjing University of Aeronautics and Astronautics |
| ORCID | 0000-0003-0948-2571 |
| VERIFIED | Yes |
| TOTAL WORKS | 13 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 13 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Uncovering the determinants of infant and toddler childcare demand in less-developed rural China
Introduction: China faces a severe imbalance between the supply and demand of formal childcare services for infants and toddlers aged 0-3, with rural research and resource allocation falling far behind urban areas. Objective: This study aimed to identify key determinants of rural childcare demand in western China's less-developed regions and to screen the optimal predictive machine learning (ML) prediction model, based on Andersen's Behavioral Mo…
Artificial intelligence in acute and critical care
Background: The Emergency Department (ED) and Intensive Care Unit (ICU) are high-acuity environments where rapid decision-making and clinical precision are fundamental to patient survival. Artificial Intelligence (AI) offers transformative potential by providing real-time data synthesis, advanced pattern recognition, and personalized decision support-capabilities essential for optimizing clinical efficiency and patient outcomes. This narrative re…
Enhancing Student Dropout Prediction in Educational Data Mining Using Sparse Feedback Based Deep Residual Network With Xception and Optimised Feature Selection
Student dropout is one of the trickiest and most detrimental problems in education; it has an impact on both students and institutions. Predicting student dropout rates early helps mitigate the negative social and economic effects. In order to solve the issue, this article suggests a novel method for predicting the dropout rate of students. Data transformation, feature selection and student dropout prediction are three steps involved here. Input …
Adolescents' mental health, problematic internet use, and their parents' rules on internet use
Core and bridge symptoms of demoralization in Chinese female cancer patients
Discouragement (C3)", "No self-worth (A3)", "Hopeless (D4)", and "Vulnerability (B3)" are both core symptoms and bridge symptoms. These symptoms can not only trigger a patient's demoralization but also stimulate more severe symptom clusters through interactions. The early recognition of and intervention regarding these symptoms could be important for the prevention and treatment of demoralization among female cancer patients
Predicting the risk factors of diabetic ketoacidosis-associated acute kidney injury
Objective The purpose of this study was to develop and validate a predictive model based on a machine learning (ML) approach to identify patients with DKA at increased risk of AKI within 1 week of hospitalization in the intensive care unit (ICU). Methods Patients diagnosed with DKA from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database according to the International Classification of Diseases (ICD)-9/10 code were included. Th…
Analysis of the Degradation of OCPs Contaminated Soil by the BC/nZVI Combined with Indigenous Microorganisms
Organochlorine pesticides (OCPs) were typical persistent organic pollutants that posed great hazards and high risks in soil. In this study, a peanut shell biochar-loaded nano zero-valent iron (BC/nZVI) material was prepared in combination with soil indigenous microorganisms to enhance the degradation of α-hexachlorocyclohexane(α-HCH) and γ-hexachlorocyclohexane(γ-HCH) in water and soil. The effects of BC/nZVI on indigenous microorganisms in soil …
International students’ psychosocial well-being and social media use at the onset of the Covid-19 pandemic
The effects of an AWE-aided assessment approach on business English writing performance and writing anxiety
Development and Internal Validation of a Nomogram to Predict Mortality During the ICU Stay of Thoracic Fracture Patients Without Neurological Compromise
Background: This study aimed to develop and validate a nomogram for predicting mortality in patients with thoracic fractures without neurological compromise and hospitalized in the intensive care unit. Methods: A total of 298 patients from the Medical Information Mart for Intensive Care III (MIMIC-III) database were included in the study, and 35 clinical indicators were collected within 24 h of patient admission. Risk factors were identified usin…
Diagnosing English reading ability in Chinese senior high schools
The Small Predicts Large Effect in Crowdfunding
Entrepreneurs are increasingly relying on online crowdfunding-the use of online platforms to raise money from a large number of people-to finance their ventures. This research explores the proposition that the amounts contributed by the majority of funders in the early stages of a crowdfunding campaign may have a counterintuitive influence on follow-up contributions and on the campaign's fundraising success. Findings from an analysis of real-worl…
Understanding the Factors Influencing Patient E-Health Literacy in Online Health Communities (OHCs)
Although online health communities (OHCs) are increasingly popular in public health promotion, few studies have explored the factors influencing patient e-health literacy in OHCs. This paper aims to address the above gap. Based on social cognitive theory, we identified one behavioral factor (i.e., health knowledge seeking) and one social environmental factor (i.e., social interaction ties) and proposed that both health knowledge seeking and socia…
The Small Predicts Large Effect in Crowdfunding
Entrepreneurs are increasingly relying on online crowdfunding-the use of online platforms to raise money from a large number of people-to finance their ventures. This research explores the proposition that the amounts contributed by the majority of funders in the early stages of a crowdfunding campaign may have a counterintuitive influence on follow-up contributions and on the campaign's fundraising success. Findings from an analysis of real-worl…
Understanding the Factors Influencing Patient E-Health Literacy in Online Health Communities (OHCs)
Although online health communities (OHCs) are increasingly popular in public health promotion, few studies have explored the factors influencing patient e-health literacy in OHCs. This paper aims to address the above gap. Based on social cognitive theory, we identified one behavioral factor (i.e., health knowledge seeking) and one social environmental factor (i.e., social interaction ties) and proposed that both health knowledge seeking and socia…
Diagnosing English reading ability in Chinese senior high schools
The Small Predicts Large Effect in Crowdfunding
Entrepreneurs are increasingly relying on online crowdfunding-the use of online platforms to raise money from a large number of people-to finance their ventures. This research explores the proposition that the amounts contributed by the majority of funders in the early stages of a crowdfunding campaign may have a counterintuitive influence on follow-up contributions and on the campaign's fundraising success. Findings from an analysis of real-worl…
Development and Internal Validation of a Nomogram to Predict Mortality During the ICU Stay of Thoracic Fracture Patients Without Neurological Compromise
Background: This study aimed to develop and validate a nomogram for predicting mortality in patients with thoracic fractures without neurological compromise and hospitalized in the intensive care unit. Methods: A total of 298 patients from the Medical Information Mart for Intensive Care III (MIMIC-III) database were included in the study, and 35 clinical indicators were collected within 24 h of patient admission. Risk factors were identified usin…
International students’ psychosocial well-being and social media use at the onset of the Covid-19 pandemic
The effects of an AWE-aided assessment approach on business English writing performance and writing anxiety
Predicting the risk factors of diabetic ketoacidosis-associated acute kidney injury
Objective The purpose of this study was to develop and validate a predictive model based on a machine learning (ML) approach to identify patients with DKA at increased risk of AKI within 1 week of hospitalization in the intensive care unit (ICU). Methods Patients diagnosed with DKA from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database according to the International Classification of Diseases (ICD)-9/10 code were included. Th…
Analysis of the Degradation of OCPs Contaminated Soil by the BC/nZVI Combined with Indigenous Microorganisms
Organochlorine pesticides (OCPs) were typical persistent organic pollutants that posed great hazards and high risks in soil. In this study, a peanut shell biochar-loaded nano zero-valent iron (BC/nZVI) material was prepared in combination with soil indigenous microorganisms to enhance the degradation of α-hexachlorocyclohexane(α-HCH) and γ-hexachlorocyclohexane(γ-HCH) in water and soil. The effects of BC/nZVI on indigenous microorganisms in soil …
Adolescents' mental health, problematic internet use, and their parents' rules on internet use
Core and bridge symptoms of demoralization in Chinese female cancer patients
Discouragement (C3)", "No self-worth (A3)", "Hopeless (D4)", and "Vulnerability (B3)" are both core symptoms and bridge symptoms. These symptoms can not only trigger a patient's demoralization but also stimulate more severe symptom clusters through interactions. The early recognition of and intervention regarding these symptoms could be important for the prevention and treatment of demoralization among female cancer patients
Uncovering the determinants of infant and toddler childcare demand in less-developed rural China
Introduction: China faces a severe imbalance between the supply and demand of formal childcare services for infants and toddlers aged 0-3, with rural research and resource allocation falling far behind urban areas. Objective: This study aimed to identify key determinants of rural childcare demand in western China's less-developed regions and to screen the optimal predictive machine learning (ML) prediction model, based on Andersen's Behavioral Mo…
Artificial intelligence in acute and critical care
Background: The Emergency Department (ED) and Intensive Care Unit (ICU) are high-acuity environments where rapid decision-making and clinical precision are fundamental to patient survival. Artificial Intelligence (AI) offers transformative potential by providing real-time data synthesis, advanced pattern recognition, and personalized decision support-capabilities essential for optimizing clinical efficiency and patient outcomes. This narrative re…
Enhancing Student Dropout Prediction in Educational Data Mining Using Sparse Feedback Based Deep Residual Network With Xception and Optimised Feature Selection
Student dropout is one of the trickiest and most detrimental problems in education; it has an impact on both students and institutions. Predicting student dropout rates early helps mitigate the negative social and economic effects. In order to solve the issue, this article suggests a novel method for predicting the dropout rate of students. Data transformation, feature selection and student dropout prediction are three steps involved here. Input …
Psychology (7 works) · Medicine (5 works) · Computer Science (4 works) · Anxiety (3 works) · Intensive care unit (3 works) · Area under the curve (2 works) · Clinical Psychology (2 works) · Developmental psychology (2 works) · EFL/ESL Teaching and Learning (2 works) · Emergency Medicine (2 works)