A Smart AI-based Conversational System for Enhancing Disease Awareness
Keywords:
Artificial intelligence, Chatbots, COVID-19 pandemic, Healthcare, Natural languageAbstract
Chatbots have emerged as scalable tools in healthcare and public health for tasks such as triage, risk assessment, information delivery, behaviour-change coaching, and mental-health support. Rapid adoption during the COVID-19 pandemic showcased their value in managing high information demand and reducing clinical workloads. Recent reviews identified promising outcomes of chatbots in certain applications, notably smoking cessation, such that results are inconsistent with diet and physical-activity interventions. Positive user engagement and feasibility have been reported by many systems, although methodological limitations and short follow-up periods constrain conclusions about long-term effectiveness. Several studies also highlight the role of continuous monitoring and user feedback in improving system performance and personalisation over time. Furthermore, integrating human oversight with AI-driven systems helps ensure reliability and supports more informed decision-making in real-world applications. Ethical considerations, including privacy, accuracy, equity, and transparency, continue to inform deployment. This literature survey synthesises current applications, findings on effectiveness, and research gaps toward guiding safer use of evidence-based chatbots across diverse healthcare and public-health settings worldwide today.
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