惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Engineering at Meta
Engineering at Meta
Microsoft Azure Blog
Microsoft Azure Blog
I
InfoQ
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
人人都是产品经理
人人都是产品经理
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
T
Tailwind CSS Blog
MongoDB | Blog
MongoDB | Blog
Google DeepMind News
Google DeepMind News
WordPress大学
WordPress大学
量子位
美团技术团队
大猫的无限游戏
大猫的无限游戏
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Last Week in AI
Last Week in AI
博客园 - 司徒正美
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
小众软件
小众软件
C
Check Point Blog
博客园 - 三生石上(FineUI控件)
N
Netflix TechBlog - Medium
Recent Announcements
Recent Announcements
有赞技术团队
有赞技术团队
月光博客
月光博客

cs.SI updates on arXiv.org

Hiding in Plain Sight: Finding MAHA on Reddit Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling Algorithmic Cultivation: How Social Media Feeds Shape User Language Universal Dynamics of Punctuated Progress AI-Mediated Communication Can Steer Collective Opinion CitePrism: Human-in-the-Loop AI for Citation Auditing and Editorial Integrity Explainable Detection of Depression Status Shifts from User Digital Traces Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles Humanwashing -- It Should Leave You Feeling Dirty When Do LLMs Generate Realistic Social Networks? A Multi-Dimensional Study of Culture, Language, Scale, and Method Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks Predicting Channel Closures in the Lightning Network with Machine Learning Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence When Can Digital Personas Reliably Approximate Human Survey Findings? RAwR: Role-Aware Rewiring via Approximate Equitable Partition GravityGraphSAGE: Link Prediction in Directed Attributed Graphs Structure-Centric Graph Foundation Model via Geometric Bases Attention-based graph neural networks: a survey When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge Scalable inference of spatial regions and temporal signatures from time series Can LLMs Emulate Human Belief Dynamics? Predicting Post Virality with Temporal Cross-Attention over Trend Signals H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks
Customer Empowerment in Healthcare Organisations Through ...
Muhammad Anshari, Mohammad N. Almunawar, Patrick K. C. Low, Zaw · 2012-07-26 · via cs.SI updates on arXiv.org

Customer Relationship Management (CRM) with the Web technology provides healthcare organizations the ability to broaden services beyond its usual practices, and thus provides a particular advantageous environment to achieve complex e-health goals. This paper discusses and demonstrates how a new approach in CRM based on Web 2.0 namely CRM 2.0 will help customers to have greater control in the sense of controlling the process of interaction (empowerment) between healthcare organizations with its customers, and among customers themselves. A survey was conducted to gather preliminary requirements and expectations on empowerment in Brunei. The survey revealed that there is a high demand for empowering customers in Brunei through the Web. Regardless of the limitations of the survey, the general public has responded with a great support for the capabilities of empowerment listed from the questionnaires. The data were analyzed to provide initial ideas and recommendation to a future direction on research for customers' empowerment in e-health services.