The Impact of Penetration Rate of Online Health Service on Service Quality and Price: Evidence from Online Health Communities. - Junwei Kuang; Lini Kuang; Zhijun Yan (ICCSE, 2018)

Dynamic prediction of cardiovascular disease using improved LSTM. - Junwei Kuang; Hangzhou Yang; Junjiang Liu; Zhijun Yan (Int. J. Crowd Sci., 2019)

More User Engagement in Online Community: Effects of Posting and Replying Behaviors on Detection of Depression. - Junwei Kuang; Zhijun Yan; Shiwei Sun (PACIS, 2022)

What Symptoms and How Long? An Interpretable AI Approach for Depression Detection in Social Media. - Junwei Kuang; Jiaheng Xie; Zhijun Yan (ICIS, 2023)

Suicide Risk Prediction for Users with Depression in Question Answering Communities: A Design Based on Deep Learning. - Haoyue Fan; Qiuju Yin; Zhijun Yan; Junwei Kuang (PACIS, 2023)

Understanding Social Support Needs in Health Question: An Answer-Enhanced Semi-Supervised Deep Learning Approach. - Junwei Kuang; Liang Yang; Shaoze Cui; Weiguo Fan (ICIS, 2024)

Does the Night Give Power? Social Media Depression and Its Symptom Detection Considering Temporal Patterns. - Liang Yang; Qiuju Yin; Zhijun Yan; Shaoze Cui; Junwei Kuang (ICIS, 2024)

A Lightweight and Efficient Multi-Type Defect Detection Method for Transmission Lines Based on DCP-YOLOv8. - Yong Wang; Linghao Zhang; Xingzhong Xiong; Junwei Kuang; Siyu Xiang (Sensors, 2024)

Protecting Children from Violent Short Videos: A Child-Attentive Multimodal Multitask Learning Approach. - Chenxing Zhao; Liang Yang; Junwei Kuang; Zhijun Yan (PACIS, 2025)

An interpretable imbalance ensemble classification method for readmission risk assessment incorporating multi-view perturbation and SHAP analysis. - Shaoze Cui; Ruize Gao; Junwei Kuang; Liang Yang; Huaxin Qiu 004; Xiaowen Wei (Decis. Support Syst., 2025)

A two-stage multi-task learning model for predicting and interpreting received answers in online mental health communities. - Qiuju Yin; Liang Yang; Junwei Kuang; Zhijun Yan (Expert Syst. Appl., 2025)

Understanding Social Support Needs in Questions: A Hybrid Approach Integrating Semi-Supervised Learning and LLM-based Data Augmentation. - Junwei Kuang; Liang Yang; Shaoze Cui; Weiguo Fan (CoRR, 2025)