TESTING CONVERSATIONAL AI AND VOICE UIS IN HEALTHCARE: AUTOMATION STRATEGIES FOR CHATBOTS AND VIRTUAL ASSISTANTS

Conversational AI technologies, including chatbots and voice assistants, are fundamentally transforming the healthcare landscape by introducing innovative interaction methods for both patients and providers [1]. These technologies facilitate more efficient communication, improve patient engagement, and streamline processes, but they also come with significant challenges. The complexity of healthcare-specific dialogues—often filled with medical terminology, patient emotions, and diverse scenarios—requires robust and rigorous testing to ensure effectiveness [2]. Moreover, adherence to regulatory standards is crucial in the healthcare sector, as any failure in communication can lead to serious implications for patient safety and care quality [3]. This white paper delves into various automation strategies designed for testing conversational AI and voice user interfaces (UIs) in healthcare environments.

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Publication Details

Journal
International Journal of Advanced Research in Computer Science
Published
2025-06-20
DOI
https://doi.org/10.26483/ijarcs.v16i3.7265
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
2.48
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article

TESTING CONVERSATIONAL AI AND VOICE UIS IN HEALTHCARE: AUTOMATION STRATEGIES FOR CHATBOTS AND VIRTUAL ASSISTANTS

Vamsi Krishna Pottla
1 citations
International Journal of Advanced Research in Computer Science
AI in Service Interactions
2.48
article

TESTING CONVERSATIONAL AI AND VOICE UIS IN HEALTHCARE: AUTOMATION STRATEGIES FOR CHATBOTS AND VIRTUAL ASSISTANTS

Vamsi Krishna Pottla
article en
1 citations

Abstract

Conversational AI technologies, including chatbots and voice assistants, are fundamentally transforming the healthcare landscape by introducing innovative interaction methods for both patients and providers [1]. These technologies facilitate more efficient communication, improve patient engagement, and streamline processes, but they also come with significant challenges. The complexity of healthcare-specific dialogues—often filled with medical terminology, patient emotions, and diverse scenarios—requires robust and rigorous testing to ensure effectiveness [2]. Moreover, adherence to regulatory standards is crucial in the healthcare sector, as any failure in communication can lead to serious implications for patient safety and care quality [3]. This white paper delves into various automation strategies designed for testing conversational AI and voice user interfaces (UIs) in healthcare environments.

International Journal of Advanced Research in Computer ScienceVol. 16(03)
Dallas Surgical Group (US), University of Texas Health Science Center at Dallas (US)
Openalex Percentile: Top 10%
AI in Service Interactions
2.48
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