AI That Listens, Documents, and Engages

Authors

  • Shashikala Valiki Author

DOI:

https://doi.org/10.5281/zenodo.20537629

Keywords:

Generative Artificial Intelligence In Healthcare, Clinical Documentation Automation, Patient Engagement Systems, Automated Clinical Note Generation, Unstructured Medical Text Processing, Conversational AI In Healthcare, Clinical Workflow Efficiency, Health Literacy–Aware Content Generation, Patient Education Automation, Appointment Scheduling Systems, Intelligent Patient Triage, Healthcare AI Implementation, Clinical Standardization Templates, Data Governance In Healthcare AI, Ethical AI In Medicine, Bias And Risk Management, Adversarial AI Concerns, Compliance In Clinical Documentation, Real-World Healthcare AI Deployments, Human-Centered Clinical AI Systems.

Abstract

Generative AI systems, capable of producing coherent, contextually relevant text, images, and other media from prompt inputs, have become increasingly accessible. The potential for Generative AI to improve patient care and clinician efficiency has generated considerable interest in the healthcare sector, focusing on the enhancement of clinical documentation and patient engagement processes. The use of Generative AI in these domains is discussed with a focus on the underlying technology, implementation considerations for healthcare organizations, and case studies demonstrating the effectiveness of Generative AI in real-world deployments.

Automated generation of clinical notes based on free-text summaries, unstructured summaries of patient examinations and assessments, or conversational inputs is explored, along with the code-based structuring of free-text notes and the application of standardization templates to ensure compliance. The generation of patient education materials appropriate for health literacy levels and cultural backgrounds, the scheduling of appointments, and the triaging of patient queries using Generative AI are also covered. Ethical considerations—especially with respect to data governance and the potential for biased, adversarial, or inaccurate output—are flagged throughout, along with the importance of establishing and maintaining high-quality workflows for the use of Generative AI services.

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Additional Files

Published

2026-03-12

Data Availability Statement

None

How to Cite

AI That Listens, Documents, and Engages. (2026). American Data Science Journal for Advanced Computations (ADSJAC), 4(01). https://doi.org/10.5281/zenodo.20537629