Saved in:
| Main Authors: | Feng, Kaidong, Sun, Zhu, Lee, Roy Ka-Wei, Jiang, Xun, Theng, Yin-Leng, Ding, Yi |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.03603 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors
by: Xuan, Wei, et al.
Published: (2025)
by: Xuan, Wei, et al.
Published: (2025)
Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
by: Chowdhury, Meghna Roy, et al.
Published: (2025)
by: Chowdhury, Meghna Roy, et al.
Published: (2025)
Design and Usability of Digital Libraries: Case Studies in the Asia Pacific
by: Theng, Yin-Leng, Ed., et al.
Published: (2005)
by: Theng, Yin-Leng, Ed., et al.
Published: (2005)
Digital Phenotyping for Adolescent Mental Health: A Feasibility Study Employing Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data
by: Kadirvelu, Balasundaram, et al.
Published: (2025)
by: Kadirvelu, Balasundaram, et al.
Published: (2025)
LLM Agent-Based Simulation of Student Activities and Mental Health Using Smartphone Sensing Data
by: Sommuang, Wayupuk, et al.
Published: (2025)
by: Sommuang, Wayupuk, et al.
Published: (2025)
Integration of Large Language Models and Traditional Deep Learning for Social Determinants of Health Prediction
by: Landes, Paul, et al.
Published: (2025)
by: Landes, Paul, et al.
Published: (2025)
Comparing Machine Learning Models for Short‐Term U.S. Treasury Yield Forecasting
by: Max Yue‐Feng Wang, et al.
Published: (2025)
by: Max Yue‐Feng Wang, et al.
Published: (2025)
Interpreting Bias in Large Language Models: A Feature-Based Approach
by: Prakash, Nirmalendu, et al.
Published: (2024)
by: Prakash, Nirmalendu, et al.
Published: (2024)
GeogDL: A Web-Based Approach to Geography Examination Revision
by: Goh, Dion H., et al.
Published: (2005)
by: Goh, Dion H., et al.
Published: (2005)
Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder
by: Kannan, Kamala Devi, et al.
Published: (2024)
by: Kannan, Kamala Devi, et al.
Published: (2024)
Association Between Smartphone Attachment and Mental Health in Adolescents
by: Xiaoxuan Liu, et al.
Published: (2025)
by: Xiaoxuan Liu, et al.
Published: (2025)
Adaptive In-Context Learning with Large Language Models for Bundle Generation
by: Sun, Zhu, et al.
Published: (2023)
by: Sun, Zhu, et al.
Published: (2023)
Comparison Analysis of Traditional Machine Learning and Deep Learning Techniques for Data and Image Classification
by: Karypidis, Efstathios, et al.
Published: (2022)
by: Karypidis, Efstathios, et al.
Published: (2022)
Harnessing Small‐Data Machine Learning for Transformative Mental Health Forecasting: Towards Precision Psychiatry With Personalised Digital Phenotyping
by: Peng Wang, et al.
Published: (2025)
by: Peng Wang, et al.
Published: (2025)
Exploring Sign Language Detection on Smartphones: A Systematic Review of Machine and Deep Learning Approaches
by: Iftikhar Alam, et al.
Published: (2024)
by: Iftikhar Alam, et al.
Published: (2024)
Tutorial on Using Machine Learning and Deep Learning Models for Mental Illness Detection
by: Zhang, Yeyubei, et al.
Published: (2025)
by: Zhang, Yeyubei, et al.
Published: (2025)
Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance?
by: Liu, Junhua, et al.
Published: (2024)
by: Liu, Junhua, et al.
Published: (2024)
Can Seniors Spot Deepfakes? A Diary Study of Deepfake Identification Strategies
by: Rachel Wan Ying Chun, et al.
Published: (2024)
by: Rachel Wan Ying Chun, et al.
Published: (2024)
A Comparative Analysis of Traditional and Deep Learning Time Series Architectures for Influenza A Infectious Disease Forecasting
by: Agyemang, Edmund F., et al.
Published: (2025)
by: Agyemang, Edmund F., et al.
Published: (2025)
Multimodal Machine Learning in Mental Health: A Survey of Data, Algorithms, and Challenges
by: Sahili, Zahraa Al, et al.
Published: (2024)
by: Sahili, Zahraa Al, et al.
Published: (2024)
Dynamic Digital Libraries for Children.
by: Theng, Yin Leng, et al.
Published: (2001)
by: Theng, Yin Leng, et al.
Published: (2001)
Machine Unlearning for Traditional Models and Large Language Models: A Short Survey
by: Xu, Yi
Published: (2024)
by: Xu, Yi
Published: (2024)
Forecast-Then-Optimize Deep Learning Methods
by: Jiang, Jinhang, et al.
Published: (2025)
by: Jiang, Jinhang, et al.
Published: (2025)
Comparing Machine Learning and Traditional Models to Predict One‐Year Post‐Stroke Dementia Risk
by: Xueting Ding, et al.
Published: (2025)
by: Xueting Ding, et al.
Published: (2025)
Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case
by: Roy, Kaushik, et al.
Published: (2025)
by: Roy, Kaushik, et al.
Published: (2025)
MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention
by: Wu, Ruolan, et al.
Published: (2023)
by: Wu, Ruolan, et al.
Published: (2023)
Evaluating Federated Learning for Cross-Country Mood Inference from Smartphone Sensing Data
by: Kalpande, Sharmad, et al.
Published: (2026)
by: Kalpande, Sharmad, et al.
Published: (2026)
AWARE Narrator and the Utilization of Large Language Models to Extract Behavioral Insights from Smartphone Sensing Data
by: Zhang, Tianyi, et al.
Published: (2024)
by: Zhang, Tianyi, et al.
Published: (2024)
A Comparative Study of Machine Learning and Deep Learning for Out-of-Distribution Detection
by: Baek, Jihyeon, et al.
Published: (2026)
by: Baek, Jihyeon, et al.
Published: (2026)
SEMA-SQL: Beyond Traditional Relational Querying with Large Language Models
by: Lin, Yin, et al.
Published: (2026)
by: Lin, Yin, et al.
Published: (2026)
Proposing a 6+3 Model for Developing Information Literacy Standards for Schools: A Case for Singapore
by: Mokhtar, Intan Azura, et al.
Published: (2009)
by: Mokhtar, Intan Azura, et al.
Published: (2009)
Structured Visual Narratives Undermine Safety Alignment in Multimodal Large Language Models
by: Tan, Rui Yang, et al.
Published: (2026)
by: Tan, Rui Yang, et al.
Published: (2026)
Benchmarking Android Malware Detection: Traditional vs. Deep Learning Models
by: Liu, Guojun, et al.
Published: (2025)
by: Liu, Guojun, et al.
Published: (2025)
A Comparative Study of Machine Learning Algorithms for Electricity Price Forecasting with LIME-Based Interpretability
by: Zhao, Xuanyi, et al.
Published: (2025)
by: Zhao, Xuanyi, et al.
Published: (2025)
RETRACTION: Data Classification of Mental Health and Personality Evaluation Based on Network Deep Learning
by: Mobile Information Systems
Published: (2025)
by: Mobile Information Systems
Published: (2025)
A Tradition-Historical Study of Mal 1.1-2.16: Traditions, Significance and Messages
by: Wong, Ka Yu
Published: (2025)
by: Wong, Ka Yu
Published: (2025)
StreamSense: Streaming Social Task Detection with Selective Vision-Language Model Routing
by: Wang, Han, et al.
Published: (2026)
by: Wang, Han, et al.
Published: (2026)
Comparative Evaluation of Traditional and Deep Learning Feature Matching Algorithms using Chandrayaan-2 Lunar Data
by: Makharia, R., et al.
Published: (2025)
by: Makharia, R., et al.
Published: (2025)
Comparing Ocean Forecasts Driven with Machine Learning-based and Physics-based Atmospheric Forcings
by: Zhou, Xiaobing, et al.
Published: (2026)
by: Zhou, Xiaobing, et al.
Published: (2026)
Benchmarking Traditional Machine Learning and Deep Learning Models for Fault Detection in Power Transformers
by: Saravanan, Bhuvan, et al.
Published: (2025)
by: Saravanan, Bhuvan, et al.
Published: (2025)
Similar Items
-
Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors
by: Xuan, Wei, et al.
Published: (2025) -
Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
by: Chowdhury, Meghna Roy, et al.
Published: (2025) -
Design and Usability of Digital Libraries: Case Studies in the Asia Pacific
by: Theng, Yin-Leng, Ed., et al.
Published: (2005) -
Digital Phenotyping for Adolescent Mental Health: A Feasibility Study Employing Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data
by: Kadirvelu, Balasundaram, et al.
Published: (2025) -
LLM Agent-Based Simulation of Student Activities and Mental Health Using Smartphone Sensing Data
by: Sommuang, Wayupuk, et al.
Published: (2025)