Understanding Patient Perception of Medical Artificial Intelligence: A Proposed Qualitative Study

Escobar, Jessica M.

doi:10.1145/3380851.3418616

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…We also discussed the types of AI models used in the identified CHI systems. To the best of our knowledge, this is the first review to analyze patient perceptions of and outcomes after using AI-based CHI systems [27][28][29][30][31].…”

Section: Objectivementioning

confidence: 99%

Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review

Asan,

Choi,

Wang

2023

J Med Internet Res

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Background There is no doubt that the recent surge in artificial intelligence (AI) research will change the trajectory of next-generation health care, making it more approachable and accessible to patients. Therefore, it is critical to research patient perceptions and outcomes because this trend will allow patients to be the primary consumers of health technology and decision makers for their own health. Objective This study aimed to review and analyze papers on AI-based consumer health informatics (CHI) for successful future patient-centered care. Methods We searched for all peer-reviewed papers in PubMed published in English before July 2022. Research on an AI-based CHI tool or system that reports patient outcomes or perceptions was identified for the scoping review. Results We identified 20 papers that met our inclusion criteria. The eligible studies were summarized and discussed with respect to the role of the AI-based CHI system, patient outcomes, and patient perceptions. The AI-based CHI systems identified included systems in mobile health (13/20, 65%), robotics (5/20, 25%), and telemedicine (2/20, 10%). All the systems aimed to provide patients with personalized health care. Patient outcomes and perceptions across various clinical disciplines were discussed, demonstrating the potential of an AI-based CHI system to benefit patients. Conclusions This scoping review showed the trend in AI-based CHI systems and their impact on patient outcomes as well as patients’ perceptions of these systems. Future studies should also explore how clinicians and health care professionals perceive these consumer-based systems and integrate them into the overall workflow.

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Section: Objectivementioning

confidence: 99%

Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review

Asan,

Choi,

Wang

2023

J Med Internet Res

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The Potentials and Pitfalls of Computer Visioning and Machine Learning Methods for Communication Researchers

Carradini,

Lauer,

Nystrom

2023

Proceedings of the 41st ACM International Conference on Design of Communication

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Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review (Preprint)

Asan,

Choi,

Wang

2023

Preprint

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BACKGROUND There is no doubt that the recent surge in artificial intelligence (AI) research will change the trajectory of next-generation health care, making it more approachable and accessible to patients. Therefore, it is critical to research patient perceptions and outcomes because this trend will allow patients to be the primary consumers of health technology and decision makers for their own health. OBJECTIVE This study aimed to review and analyze papers on AI-based consumer health informatics (CHI) for successful future patient-centered care. METHODS We searched for all peer-reviewed papers in PubMed published in English before July 2022. Research on an AI-based CHI tool or system that reports patient outcomes or perceptions was identified for the scoping review. RESULTS We identified 20 papers that met our inclusion criteria. The eligible studies were summarized and discussed with respect to the role of the AI-based CHI system, patient outcomes, and patient perceptions. The AI-based CHI systems identified included systems in mobile health (13/20, 65%), robotics (5/20, 25%), and telemedicine (2/20, 10%). All the systems aimed to provide patients with personalized health care. Patient outcomes and perceptions across various clinical disciplines were discussed, demonstrating the potential of an AI-based CHI system to benefit patients. CONCLUSIONS This scoping review showed the trend in AI-based CHI systems and their impact on patient outcomes as well as patients’ perceptions of these systems. Future studies should also explore how clinicians and health care professionals perceive these consumer-based systems and integrate them into the overall workflow.

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Understanding Patient Perception of Medical Artificial Intelligence: A Proposed Qualitative Study

Cited by 3 publications

References 4 publications

Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review

Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review

The Potentials and Pitfalls of Computer Visioning and Machine Learning Methods for Communication Researchers

Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review (Preprint)

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