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Table 2 Papers included in the review

From: The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions

Reference

Type of study

Aim of study

Country of origin

(Alrassi 2021) [26]

Scholarly perspective

Presents some of the opportunities and challenges that AI provide. Explains how the role of physicians will evolve in an AI-augmented care environment

USA

(Amann, Blasimme et al. 2020) [27]

Conceptual and ethical analysis

Provides an assessment of the role of explainability in medical AI and ethically analyses what explainability means for the adoption of AI-driven tools into clinical practice

Switzerland, Germany, UK

(Aminololama-Shakeri and López 2019) [8]

Opinion piece

Examines what AI means for breast imaging radiologists and the doctor-patient relationship

USA

(Arnold 2021) [28]

Ethical analysis

Analyses bioethically AI systems and their impact on doctors and patients

Australia

(Banja 2019) [29]

Opinion piece

Advocates for a new field of ethics engaging specifically with health applications, and engages with commonly made bioethical criticism about AI in healthcare

USA

(Bjerring and Busch 2021) [30]

Ethical analysis

Investigates ethically the impact of black-box AI tools on the practice of medicine and patient-centred care

Denmark

(Carter, Rogers et al. 2020) [7]

Research article

Investigates the ethical, legal and social ramifications of using artificial intelligence tools in breast cancer care

Australia

(Chen 2017) [9]

Opinion piece with a case study (University of Hong Kong)

Investigates the role of doctors in future healthcare and the direction medical schools should take to prepare their graduates, in an Asian context

Hong Kong

(Dagher, Shi et al. 2020) [31]

Exploratory review and opinion piece

Assesses the role of wearables in cardiology and outlining the benefits associated with their use

USA

(Davenport and Kalakota 2019) [3]

Research article

Identifies the potential of the use of AI in healthcare and the related potential ethical implications

USA

(Eysenbach, Wright et al. 2018) [32]

Randomised controlled trial

(n = 75)

Randomised controlled trial with 75 participants recruited across the United States in order to assess the feasibility and efficacy of using an integrative psychological AI, Tess, to reduce self-identified symptoms of depression and anxiety in college students

USA

(Fogel and Kvedar 2018) [18]

Perspective

Proposes a perspective that AI tools will open the way for a more unified, human experience

USA

(Grote and Berens 2020) [33]

Ethical analysis

Investigates ethically the use of AI tools in clinical decision-making and identification of potential pitfalls of involving machine learning in healthcare

Germany

(Hagendorff and Wezel 2019) [34]

Overview article

Provides a general overview of the current problems that AI and machine learning research and development must deal with

Germany

(Ho 2019) [4]

Opinion piece

Explores the ethical challenges posed by AI tools in healthcare and suggests solutions

?

(Hung, Chen et al. 2021) [35]

Opinion piece

Outlines the benefits of using AI tools in the field of urology

USA

(Johnston 2018) [36]

Commentary

Explores the training needs of future physicians in the age of artificial intelligence

USA

(Jotterand and Bosco 2020) [25]

Commentary

Outlines the conditions necessary for AI to be ethically integrated in healthcare systems

USA

(Karches 2018) [37]

Philosophical analysis

Philosophically analyses why AI tools should not replace human doctors’ judgements

USA

(Kerasidou 2020) [38]

Ethical analysis

Analyses ethically how AI has the potential to fundamentally alter the way in which empathy, compassion and trust are currently regarded and practised in health care

United Kingdom

(Kim, Jones et al. 2019) [39]

Opinion piece

Discusses effects that new technological developments, such as AI, have had on the profession of psychiatry and how teachers can teach trainee psychiatrists the best practices

USA

(Kolanska, Chabbert-Buffet et al. 2021) [40]

Overview article

Summarises AI use in healthcare, its technical, professional, and ethical shortcomings and assesses of how it ought to be used

France

(Kool, Laranjo et al. 2019) [41]

Survey (n = 720)

Conducts a web-based survey of 720 UK GPs' perspectives on whether technology will ever completely replace doctors in providing primary care tasks

United Kingdom

(Lagrew and Jenkins 2015) [42]

Overview and opinion piece

Outlines the future of obstetrics/gynaecology in 2020 including computer-aided diagnoses and proposes a way to thrive in the new system

USA

(Liu, Keane et al. 2018) [43]

Commentary

Outlines how to prepare the future generation of doctors to practice in a health system enabled by artificial intelligence while providing humanity to the machine-patient relationship

United Kingdom

(Luxton 2014) [44]

Review (number of papers used: unspecified)

Identifies and reviews ethical concerns associated with AI care providers (AICPs) in mental health care and other professions. Makes recommendations for the development of ethical codes and the design of AICPs

USA

(Mabillard, Demartines et al. 2021) [45]

Perspective

Discusses the issue of preserving trusting and high-quality relationships between doctors and patients in an era of spread of online information and demands related to accountability placed on healthcare professionals

Belgium, Switzerland

(Manrique de Lara and Peláez-Ballestas 2020) [46]

Narrative review (number of papers used: unspecified)

Provides a narrative review of the bioethical perspectives of big data with a specific focus on the field of Rheumatology

 Mexico

(McDougall 2019 [24])

Ethical analysis

Conducts an ethical analysis of the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations

Australia

(Mihai 2019 [47])

Ethical analysis

Investigates ethically which, if any, aspects of medicine—currently or in the future—can and ought to be left in the hands of AI

USA

(Molnár-Gábor 2020) [48]

Research article

Examines the practical and ethical issues that the application of AI raises for people and society

Germany

(Nelson, Pérez-Chada et al. 2020) [10]

Qualitative study using semi-structured interviews (n = 48)

Investigates how patients view the usage of AI for skin cancer detection and how they conceptualise the technology. Qualitative study with semi structured interviews conducted in hospitals in Boston, USA. 48 patients were enrolled

USA

(Niel and Bastard 2019) [22]

Perspective

Provides an overview of evidence on medical artificial intelligence relevant to the field of nephrology. Defines core concepts, recent clinical applications and provides a perspective on future considerations including ethical issues arising

France

(Printz 2017) [49]

Commentary

Summarises the evidence of the time saving capabilities of Watson for Oncology and provides a perspective on AI as an assistant for treatment decisions

USA

(Rainey and Erden 2020) [50]

Ethical analysis

Identifies issues with the application of neural technologies in psychiatry and urges caution, especially regarding normative issues

UK

(Sparrow and Hatherley 2020) [23]

Opinion piece

Provides a critical analysis of the positive discourse surrounding the doctor-patient relationship and implementation of AI in healthcare

Australia

(Szalai 2020) [51]

Research article

Explores theoretically and practically the possibility of AI-based addendum therapy for borderline personality disorder and identifies its potential advantages and limitations

Hungary

(Trachsel, Gaab et al.) [52]

Research article

Explores the use of chatbots and AI tools as supplements to psychotherapy delivered by humans, and as supervised primary treatments. Discusses how ethical guidelines and standards for AI in mental health are relevant in the ethics of AI in psychotherapy

Switzerland, USA

(Triberti, Durosini et al. 2020) [53]

Perspective

Explores the “third wheel” effect that AI introduces in healthcare and identifies the impact of this effect created by AI on the healthcare process, with a focus on future medical practice

Italy

(Tripti and Lalitbhushan 2020) [54]

Opinion piece

Explores the future role of medical doctors in an AI-augmented environment and the related implications on medical education

India

(Wartman 2019) [55]

Commentary

Identifies challenges facing medical education and ways forward to address these challenges, including the preservation of the doctor-patient relationship in an AI-augmented world

USA

(Wartman 2019) [56]

Opinion piece

Explores ethically how medical education systems should adapt to the integration of AI systems in healthcare

USA

(Young, Amara et al. 2021) [57]

Mixed-method systematic review (n = 23)

Explores patient and general public attitudes towards clinical artificial intelligence using a mixed-method systematic review in biomedical and computational databases. 23 papers met the inclusion criteria

USA

(Yun, Lee et al. 2021) [58]

Behavioural study (n = 350) and neural study (n = 22)

Explores (1) Behavioural and (2) neural consumer responses to human doctors and medical artificial intelligence. Study (1) recruited 350 Amazon Mechanical Turk (MTurk) and study (2) recruited 22 participants in their twenties

Korea

(Žaliauskaitė 2020) [59]

Theoretical analysis

Discusses challenging aspects of patients’ right to autonomy in the context of technologies and innovation and the role of the implementation of legal instruments against this background

Lithuania