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The Use of Chatbots in Oncological Care: A Narrative Review.

作者信息

Wang Alexander, Qian Zhiyu, Briggs Logan, Cole Alexander P, Reis Leonardo O, Trinh Quoc-Dien

机构信息

Division of Urological Surgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

出版信息

Int J Gen Med. 2023 May 1;16:1591-1602. doi: 10.2147/IJGM.S408208. eCollection 2023.


DOI:10.2147/IJGM.S408208
PMID:37152273
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10162388/
Abstract

BACKGROUND: Few reports have investigated chatbots in patient care. We aimed to assess the current applications, limitations, and challenges in the literature on chatbots employed in oncological care. METHODS: We queried the PubMed database through April 2022 and included studies that investigated the use of chatbots in different phases of oncological care. The search used five different combinations of the specific terms "chatbot", "cancer", "oncology", and "conversational agent". Inclusion criteria were chatbot use in any aspect of oncological care-prevention, patient education, treatment, and surveillance. RESULTS: The initial search yielded 196 records, 21 of which met inclusion criteria. The identified chatbots mostly focused on breast and ovarian cancer (n=8), with the second most common being cervical cancer (n=3). Good patient satisfaction was reported among 14 of 21 chatbots. The most reported chatbot applications were cancer screening, prevention, risk stratification, treatment, monitoring, and management. Of 12 studies examining efficacy of care via chatbot, 9 demonstrated improvements compared to standard care. CONCLUSION: Chatbots used for oncological care to date demonstrate high user satisfaction, and many have shown efficacy in improving patient-centered communication, accessibility to cancer-related information, and access to care. Currently, chatbots are primarily limited by the need for extensive user-testing and iterative improvement before widespread implementation.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac97/10162388/faa39fe701b4/IJGM-16-1591-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac97/10162388/faa39fe701b4/IJGM-16-1591-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac97/10162388/faa39fe701b4/IJGM-16-1591-g0001.jpg

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本文引用的文献

[1]
Learning the Treatment Process in Radiotherapy Using an Artificial Intelligence-Assisted Chatbot: Development Study.

JMIR Form Res. 2022-12-2

[2]
Digital technologies in cancer care: a review from the clinician's perspective.

J Comp Eff Res. 2022-5

[3]
Cancer statistics, 2022.

CA Cancer J Clin. 2022-1

[4]
Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review.

JMIR Cancer. 2021-11-29

[5]
Patient Interactions With an Automated Conversational Agent Delivering Pretest Genetics Education: Descriptive Study.

J Med Internet Res. 2021-11-18

[6]
Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits.

Obstet Gynecol. 2021-12-1

[7]
Automated health chats for symptom management of head and neck cancer patients undergoing radiation therapy.

Oral Oncol. 2021-11

[8]
Ask Rosa - The making of a digital genetic conversation tool, a chatbot, about hereditary breast and ovarian cancer.

Patient Educ Couns. 2022-6

[9]
Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care.

Med Health Care Philos. 2022-3

[10]
Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors.

BMC Med Inform Decis Mak. 2021-8-14

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