Diabetes and conversational agents: the AIDA project case study

被引:3
作者
Alloatti F. [1 ,2 ]
Bosca A. [1 ]
Di Caro L. [2 ]
Pieraccini F. [3 ]
机构
[1] H-FARM Innovation, Turin
[2] Department of Computer Science, University of Turin, Turin
[3] Novo Nordisk Spa, Rome
来源
Discover Artificial Intelligence | / 1卷 / 1期
关键词
D O I
10.1007/s44163-021-00005-1
中图分类号
学科分类号
摘要
One of the key aspects in the process of caring for people with diabetes is Therapeutic Education (TE). TE is a teaching process for training patients so that they can self-manage their care plan. Alongside traditional methods of providing educational content, there are now alternative forms of delivery thanks to the implementation of advanced Information Technologies systems such as conversational agents (CAs). In this context, we present the AIDA project: an ensemble of two different CAs intended to provide a TE tool for people with diabetes. The Artificial Intelligence Diabetes Assistant (AIDA) consists of a text-based chatbot and a speech-based dialog system. Their content has been created and validated by a scientific board. AIDA Chatbot—the text-based agent—provides a broad spectrum of information about diabetes, while AIDA Cookbot—the voice-based agent—presents recipes compliant with a diabetic patient’s diet. We provide a thorough description of the development process for both agents, the technology employed and their usage by the general public. AIDA Chatbot and AIDA Cookbot are freely available and they represent the first example of conversational agents in Italian to support diabetes patients, clinicians and caregivers. © The Author(s) 2021.
引用
收藏
相关论文
共 83 条
[1]  
Pereira J., Diaz O., Using health Chatbots for behavior change: a mapping study, J Med Syst, 43, (2019)
[2]  
Vaidyam A.N., Wisniewski H., Halamka J.D., Kashavan M.S., Torous J.B., Chatbots and conversational agents in mental health: a review of the psychiatric landscape, Can J Psychiatry, 64, 7, pp. 456-464, (2019)
[3]  
Introduction: Standards of Medical Care in diabetes—2020, 43, 1, pp. S1-S2, (2020)
[4]  
Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes, N Engl J Med, 353, 25, pp. 2643-2653, (2005)
[5]  
Holman R.R., Paul S.K., Bethel M.A., Matthews D.R., Neil H.A.W., 10-year follow-up of intensive glucose control in type 2 diabetes, N Engl J Med, 359, 15, pp. 1577-1589, (2008)
[6]  
Shichiri M., Kishikawa H., Ohkubo Y., Wake N., Long-term results of the Kumamoto Study on optimal diabetes control in type 2 diabetic patients, Diabetes Care, 23, pp. B21-B29, (2000)
[7]  
Juarez D.T., Ma C., Kumasaka A., Shimada R., Davis J., Failure to reach target glycated a1c levels among patients with diabetes who are adherent to their antidiabetic medication, Popul Health Manag, 17, 4, pp. 218-223, (2014)
[8]  
Black L.A., McTear M., Black N., Harper R., Lemon M., Appraisal of a conversational artefact and its utility in remote patient monitoring, 18Th IEEE Symposium on Computer-Based Medical Systems (CBMS’05, pp. 506-508, (2005)
[9]  
Klonoff D.C., Schwartz D.M., An economic analysis of interventions for diabetes, Diabetes Care, 23, 3, pp. 390-404, (2000)
[10]  
Powers M.A., Bardsley J.K., Cypress M., Funnell M.M., Harms D., Hess-Fischl A., Et al., Diabetes self-management education and support in adults with type 2 diabetes: A consensus report of the American Diabetes Association, the Association of Diabetes Care & Education Specialists, the Academy of Nutrition and Dietetics, the American Academy, Diabetes Care, 43, 7, pp. 1636-1649, (2020)