Unlocking human-like conversations: Scoping review of automation techniques for personalized healthcare interventions using conversational agents

Martins, Ana; Londral, Ana; L. Nunes, Isabel; V. Lapão, Luís

doi:10.1016/j.ijmedinf.2024.105385

Cited by 3 publications

(1 citation statement)

References 65 publications

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“…This trend has prompted recommender systems to expand their scope beyond text-only interactions. By analyzing and interpreting visual content, these systems gain insights into users' aesthetic preferences and visual interests[85,86]".…”

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confidence: 99%

From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions

Al-Hasan,

Sayed,

Bensaali

et al. 2024

BDCC

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Recommender systems are a key technology for many applications, such as e-commerce, streaming media, and social media. Traditional recommender systems rely on collaborative filtering or content-based filtering to make recommendations. However, these approaches have limitations, such as the cold start and the data sparsity problem. This survey paper presents an in-depth analysis of the paradigm shift from conventional recommender systems to generative pre-trained-transformers-(GPT)-based chatbots. We highlight recent developments that leverage the power of GPT to create interactive and personalized conversational agents. By exploring natural language processing (NLP) and deep learning techniques, we investigate how GPT models can better understand user preferences and provide context-aware recommendations. The paper further evaluates the advantages and limitations of GPT-based recommender systems, comparing their performance with traditional methods. Additionally, we discuss potential future directions, including the role of reinforcement learning in refining the personalization aspect of these systems.

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confidence: 99%

From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions

Al-Hasan,

Sayed,

Bensaali

et al. 2024

BDCC

View full text Add to dashboard Cite

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Analyzing digital communication: a comprehensive literature review

Strauss,

Harr,

Pieper

2024

Manag Rev Q

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Digital communication has become an essential part of both personal and professional contexts. However, unique characteristics of digital communication—such as lacking non-verbal cues or time asynchrony—clearly distinguish this new form of communication from traditional face-to-face communication. These differences raise questions about the transferability of previous findings on traditional communication to the digital communication context and emphasize the need for specialized research. To support and guide research on the analysis of digital communication, we conducted a systematic literature review encompassing 84 publications on digital communication in leading journals. By doing so, we provide an overview of the current body of research. Thereby, we focus on distinct fields of communication, methods used to collect and analyze digital communication data, as well as common methodological limitations. Building on these insights, we derive a series of comprehensive guidelines from five distinct areas for the collection and analysis of digital communication that can guide future research and organizational practice.

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AI-Driven Personalized Nutritional and Scams Planning

S.,

2024

Neuroscientific Insights and Therapeutic Approaches to Eating Disorders

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As advancements in artificial intelligence (AI) continue to revolutionize various industries, personalized nutritional planning emerges as a promising application in the realm of healthcare and wellness. This chapter delves into the intersection of AI-driven personalized nutritional planning and the regulatory landscape governing food regulations, laws, and potential scams. By leveraging AI algorithms, individuals can receive tailored dietary recommendations based on their unique health profiles, genetic makeup, and lifestyle factors. However, amidst this innovation, ensuring compliance with food regulations and laws becomes paramount to safeguard consumer health and prevent deceptive practices. Moreover, the chapter explores the challenges posed by potential scams and fraudulent claims in the burgeoning market of personalized nutrition, emphasizing the importance of robust regulatory frameworks and consumer education initiatives.

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Unlocking human-like conversations: Scoping review of automation techniques for personalized healthcare interventions using conversational agents

Cited by 3 publications

References 65 publications

From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions

From Traditional Recommender Systems to GPT-Based Chatbots: A Survey of Recent Developments and Future Directions

Analyzing digital communication: a comprehensive literature review

AI-Driven Personalized Nutritional and Scams Planning

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