Healthcare Chatbots With Nlp and Cybersecurity: Safeguarding Patient Data in the Cloud

The implementation of NLP-driven medical chatbots raises ethical questions that are examined in this study, with a particular emphasis on the confidentiality of patients, transparency, bias mitigation measures, user perspectives, along with cybersecurity. Using additional data sources when an interpretation philosophy along with deductive methodology, the study uses a descriptive design. The results highlight the need for strong data security procedures, transparent discourse, and bias mitigation techniques. They also highlight complex challenges. User-centered design is crucial, as evidenced by the central subjects of user confidence and independence. The critical examination lays the groundwork for subsequent research by suggesting empirical assessments of suggested tactics, investigation of cultural ramifications, and continued cooperation amongst various stakeholders.

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