Literature DB >> 33733203

A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis.

Adam Baker1, Yura Perov1, Katherine Middleton1, Janie Baxter1, Daniel Mullarkey1, Davinder Sangar1, Mobasher Butt1, Arnold DoRosario2, Saurabh Johri1.   

Abstract

AI virtual assistants have significant potential to alleviate the pressure on overly burdened healthcare systems by enabling patients to self-assess their symptoms and to seek further care when appropriate. For these systems to make a meaningful contribution to healthcare globally, they must be trusted by patients and healthcare professionals alike, and service the needs of patients in diverse regions and segments of the population. We developed an AI virtual assistant which provides patients with triage and diagnostic information. Crucially, the system is based on a generative model, which allows for relatively straightforward re-parameterization to reflect local disease and risk factor burden in diverse regions and population segments. This is an appealing property, particularly when considering the potential of AI systems to improve the provision of healthcare on a global scale in many regions and for both developing and developed countries. We performed a prospective validation study of the accuracy and safety of the AI system and human doctors. Importantly, we assessed the accuracy and safety of both the AI and human doctors independently against identical clinical cases and, unlike previous studies, also accounted for the information gathering process of both agents. Overall, we found that the AI system is able to provide patients with triage and diagnostic information with a level of clinical accuracy and safety comparable to that of human doctors. Through this approach and study, we hope to start building trust in AI-powered systems by directly comparing their performance to human doctors, who do not always agree with each other on the cause of patients' symptoms or the most appropriate triage recommendation.
Copyright © 2020 Baker, Perov, Middleton, Baxter, Mullarkey, Sangar, Butt, DoRosario and Johri.

Entities:  

Keywords:  AI diagnosis; bayesian networks; computer-assisted diagnosis; diagnosis; symptom checker; triage; virtual assistant

Year:  2020        PMID: 33733203      PMCID: PMC7861270          DOI: 10.3389/frai.2020.543405

Source DB:  PubMed          Journal:  Front Artif Intell        ISSN: 2624-8212


  21 in total

1.  STARE-HI--Statement on reporting of evaluation studies in Health Informatics.

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Journal:  Int J Med Inform       Date:  2008-10-18       Impact factor: 4.046

2.  Safety of patient-facing digital symptom checkers.

Authors:  Hamish Fraser; Enrico Coiera; David Wong
Journal:  Lancet       Date:  2018-11-06       Impact factor: 79.321

Review 3.  Beyond Dr. Google: the evidence on consumer-facing digital tools for diagnosis.

Authors:  Michael L Millenson; Jessica L Baldwin; Lorri Zipperer; Hardeep Singh
Journal:  Diagnosis (Berl)       Date:  2018-09-25

4.  A fairer way forward for AI in health care.

Authors:  Linda Nordling
Journal:  Nature       Date:  2019-09       Impact factor: 49.962

5.  WHO and ITU establish benchmarking process for artificial intelligence in health.

Authors:  Thomas Wiegand; Ramesh Krishnamurthy; Monique Kuglitsch; Naomi Lee; Sameer Pujari; Marcel Salathé; Markus Wenzel; Shan Xu
Journal:  Lancet       Date:  2019-03-29       Impact factor: 79.321

Review 6.  Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings?

Authors:  Brian Wahl; Aline Cossy-Gantner; Stefan Germann; Nina R Schwalbe
Journal:  BMJ Glob Health       Date:  2018-08-29

7.  A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis.

Authors:  Adam Baker; Yura Perov; Katherine Middleton; Janie Baxter; Daniel Mullarkey; Davinder Sangar; Mobasher Butt; Arnold DoRosario; Saurabh Johri
Journal:  Front Artif Intell       Date:  2020-11-30

8.  The incidence of diagnostic error in medicine.

Authors:  Mark L Graber
Journal:  BMJ Qual Saf       Date:  2013-06-15       Impact factor: 7.035

Review 9.  The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries.

Authors:  Jonathan Guo; Bin Li
Journal:  Health Equity       Date:  2018-08-01

10.  Digital and online symptom checkers and health assessment/triage services for urgent health problems: systematic review.

Authors:  Duncan Chambers; Anna J Cantrell; Maxine Johnson; Louise Preston; Susan K Baxter; Andrew Booth; Janette Turner
Journal:  BMJ Open       Date:  2019-08-01       Impact factor: 2.692

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  13 in total

1.  Self-Diagnosis through AI-enabled Chatbot-based Symptom Checkers: User Experiences and Design Considerations.

Authors:  Yue You; Xinning Gui
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  Analyzing the determinants to accept a virtual assistant and use cases among cancer patients: a mixed methods study.

Authors:  Martien J P van Bussel; Gaby J Odekerken-Schröder; Carol Ou; Rachelle R Swart; Maria J G Jacobs
Journal:  BMC Health Serv Res       Date:  2022-07-09       Impact factor: 2.908

3.  Multiple approaches to enhancing cancer communication in the next decade: translating research into practice and policy.

Authors:  Claire C Conley; Amy K Otto; Glynnis A McDonnell; Kenneth P Tercyak
Journal:  Transl Behav Med       Date:  2021-11-30       Impact factor: 3.046

4.  A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis.

Authors:  Adam Baker; Yura Perov; Katherine Middleton; Janie Baxter; Daniel Mullarkey; Davinder Sangar; Mobasher Butt; Arnold DoRosario; Saurabh Johri
Journal:  Front Artif Intell       Date:  2020-11-30

5.  Examining the effect of explanation on satisfaction and trust in AI diagnostic systems.

Authors:  Lamia Alam; Shane Mueller
Journal:  BMC Med Inform Decis Mak       Date:  2021-06-03       Impact factor: 2.796

6.  How Clinicians Perceive Artificial Intelligence-Assisted Technologies in Diagnostic Decision Making: Mixed Methods Approach.

Authors:  Deana Shevit Goldin; Hyeyoung Hah
Journal:  J Med Internet Res       Date:  2021-12-16       Impact factor: 5.428

7.  Health chatbots acceptability moderated by perceived stigma and severity: A cross-sectional survey.

Authors:  Oliver Miles; Robert West; Tom Nadarzynski
Journal:  Digit Health       Date:  2021-12-08

8.  Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients.

Authors:  Severin Hennemann; Sebastian Kuhn; Michael Witthöft; Stefanie M Jungmann
Journal:  JMIR Ment Health       Date:  2022-01-31

9.  Artificial intelligence in the GPs office: a retrospective study on diagnostic accuracy.

Authors:  Steindor Ellertsson; Hrafn Loftsson; Emil L Sigurdsson
Journal:  Scand J Prim Health Care       Date:  2021-09-29       Impact factor: 2.581

Review 10.  The Role of Artificial Intelligence in Early Cancer Diagnosis.

Authors:  Benjamin Hunter; Sumeet Hindocha; Richard W Lee
Journal:  Cancers (Basel)       Date:  2022-03-16       Impact factor: 6.639

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