Những mối quan ngại về đạo đức xung quanh quyền riêng tư và an ninh dữ liệu trong giám sát sức khỏe bằng trí tuệ nhân tạo cho bệnh Parkinson: những hiểu biết từ bệnh nhân, thành viên gia đình và các chuyên gia y tế

Akkus Z et al (2021) Artificial intelligence (AI)-empowered echocardiography interpretation: a state-of-the-art review. J Clin Med 10(7):1391 Armstrong MJ, Okun MS (2020) Diagnosis and treatment of parkinson disease: a review. JAMA 323(6):548–560 Ayers JW et al (2023) Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med 183(6):589–596 Belić M et al (2019) Artificial intelligence for assisting diagnostics and assessment of Parkinson’s disease—a review. Clin Neurol Neurosurg 184:105442 Bell E et al (2010) Hope and patients’ expectations in deep brain stimulation: healthcare providers’ perspectives and approaches. J Clin Ethics 21(2):112–124 Bian C, Ye B, Hoonakker A, Mihailidis A (2021) Attitudes and perspectives of older adults on technologies for assessing frailty in home settings: a focus group study. BMC Geriatr. https://doi.org/10.1186/s12877-021-02252-4 Braak H, Braak E (2000) Pathoanatomy of Parkinson’s disease. J Neurol Suppl 247(2):3–10 CALYPTIX Security (2018) Top 5 causes of data breaches in healthcare. https://www.calyptix.com/research/top-5-causes-of-data-breaches-in-healthcare/. Accessed 27 Jun 2022 Challen R et al (2019) Artificial intelligence, bias and clinical safety. BMJ Qual Saf 28(3):231–237 Cho MK (2021) Rising to the challenge of bias in health care AI. Nat Med 27(12):2079–2081 Corbin J, Strauss A (2008) Basics of qualitative research: techniques and procedures for developing grounded theory, 3rd edn. Sage publications, Thousand Oaks Cutler DM (2023) What artificial intelligence means for health care. JAMA Health Forum 4(7):e232652 Danks D, London AJ (2017) Algorithmic bias in autonomous systems. In: IJCAI international joint conference on artificial intelligence, pp 1–7 Denton SW, Pauwels E, He Y, Johnson WG (2018) There’s nowhere to hide: artificial intelligence and privacy in the fourth industrial revolution. Wilson Center Policy Report (March), pp 10–11 Diprose W, Buist N (2016) Artificial intelligence in medicine: humans need not apply? N Z Med J 129(1434):73–76 Dishman E, Carrillo MC (2007) Perspective on everyday technologies for Alzheimer’s care: research findings, directions, and challenges. Alzheimer’s Dement 3(3):227–234 Eijkholt M (2020) Medicine’s collision with false hope: the false hope harms (FHH) argument. Bioethics 34(7):703–711 Elul Y et al (2021) Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis. Proc Natl Acad Sci USA 118(24):1–12 Gerke S, Minssen T, Cohen G (2020) Ethical and legal challenges of artificial intelligence-driven healthcare. In: Bohr A, Memarzadeh K (eds) Artificial intelligence in healthcare. Elsevier, London, pp 295–336 Graham SS (2022) The doctor and the algorithm: promise, peril, and the future of health AI. Oxford University Press, New York Harvey JM et al (2018) Desperately seeking a cure: treatment seeking and appraisal in irritable bowel syndrome. Br J Health Psychol 23(3):561–579 Hashimoto DA, Rosman G, Rus D, Meireles OR (2018) Artificial intelligence in surgery: promises and perils. Ann Surg 268(1):70–76 Ho A (2023) Live like nobody is watching: relational autonomy in the age of artificial intelligence. Oxford University Press, New York Ho A, Bavli I, Mahal R, MJ McKeown (2023) Multi-level ethical considerations of artificial intelligence health monitoring for people living with Parkinson’s Disease. AJOB Empir Bioeth. https://doi.org/10.1080/23294515.2023.2274582 House of Lords (2018) AI in the UK: ready, willing and able? https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf. Accessed 27 Jun 2022 Jutzi TB et al (2020) Artificial intelligence in skin cancer diagnostics: the patients’ perspective. Front Med 7(233):1–9 Kantarjian H, Yu PP (2015) Artificial intelligence, big data, and cancer. JAMA Oncol 1(5):573–574 Klugman CM, Dunn LB, Schwartz J, Glenn Cohen I (2018) The ethics of smart pills and self-acting devices: autonomy, truth-telling, and trust at the dawn of digital medicine. Am J Bioeth 18(9):38–47 Kooli C, Al Muftah HAl (2022) Artificial intelligence in healthcare: a comprehensive review of its ethical concerns. Technol Sustain 1:121–131 Landi H (2022) Healthcare data breaches hit all-time high in 2021, impacting 45M people. Health Tech. https://www.fiercehealthcare.com/health-tech/healthcare-data-breaches-hit-all-time-high-2021-impacting-45m-people. Accessed 27 Jun 2022 Lee P, Bubeck S, Petro J (2023) Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine. N Engl J Med 388(13):1233–1239 Lim LJ, Tison GH, Delling FN (2020) Artificial intelligence in cardiovascular imaging. Methodist Debakey Cardiovasc J 16(2):138–145 London AJ (2018) Groundhog day for medical artificial intelligence. Hastings Center Rep. https://doi.org/10.1002/hast.842 London AJ (2019) Artificial intelligence and black-box medical decisions: accuracy versus explainability. Hastings Center Rep 49(1):15–21 London AJ (2022) Artificial intelligence in medicine: overcoming or recapitulating structural challenges to improving patient care? Cell Rep Med 3(5):100622 Luxton DD (2014) Recommendations for the ethical use and design of artificial intelligent care providers. Artif Intell Med 62(1):1–10 Luxton DD, Anderson SL, Anderson M (2016) Ethical issues and artificial intelligence technologies in behavioral and mental health care. In: Luxton DD (ed) Artificial intelligence in behavioral and mental health care. Acadamic press, London, pp 255–276 Markowetz A et al (2014) Psycho-informatics: big data shaping modern psychometrics. Med Hypotheses 82(4):405–411 Martinez-Martin N, Kreitmair K (2018) Ethical issues for direct-to-consumer digital psychotherapy apps: addressing accountability, data protection, and consent. JMIR Ment Health 5(2):e9423 McCradden MD, Stephenson EA, Anderson JA (2020) Clinical research underlies ethical integration of healthcare artificial intelligence. Nat Med 26(9):1325–1326 Mechanic D, Tanner J (2007) Vulnerable people, groups, and populations: societal view. Health Aff 26(5):1220–1230 Miles MB, Huberman MA, Saldaña J (2014) 28 Zeitschrift fur Personalforschung. In: Qualitative data analysis. A methods sourcebook. Sage publications, Thousand Oaks Mittelstadt BD, Floridi L (2016) The ethics of big data: current and foreseeable issues in biomedical contexts. Law Govern Technol Ser 29:445–480 Murphy K et al (2021) Artificial intelligence for good health: a scoping review of the ethics literature. BMC Med Ethics 22(1):1–17 Nash DM et al (2023) Perceptions of artificial intelligence use in primary care: a qualitative study with providers and staff of ontario community health centres. J Am Board Fam Med JABFM 36(2):221–228 Nichol AA, Batten JN et al (2021a) A typology of existing machine learning-based predictive analytic tools focused on reducing costs and improving quality in health care: systematic search and content analysis. J Med Internet Res 23(6):e26391 Nichol AA, Bendavid E et al (2021b) Diverse experts’ perspectives on ethical issues of using machine learning to predict HIV/AIDS risk in sub-saharan africa: a modified delphi study. BMJ Open 11(7):e052287 Ongena YP, Haan M, Yakar D, Kwee TC (2020) Patients’ views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire. Eur Radiol 30(2):1033–1040 Parry KW (2004) Constant comparison. In: Lewis-Beck MS, Bryman A, Liao TF (eds) The SAGE encyclopedia of social science research methods. Sage, Thousand Oaks, p 181 Paul Y et al (2018) Artificial intelligence in the healthcare industry in India. The Centre for Internet and Society. pp 1–45 Ravi D et al (2016) Deep learning for health informatics. IEEE J Biomed Health Inform 21(1):4–21 Richardson JP et al (2021) Patient apprehensions about the use of artificial intelligence in healthcare. Npj Digit Med 4(1):1–6 Riggare S et al (2021) Ethical aspects of personal science for persons with Parkinson’s disease: what happens when self-tracking goes from selfcare to publication? J Parkinsons Dis 11(4):1927–1933 Rubeis G (2022) iHealth: the ethics of artificial intelligence and big data in mental healthcare. Internet Interv 28:100518 Ruddick W (1999) Hope and deception. Bioethics 13(3–4):343–357 Saldaña J (2016) The coding manual for qualitative researchers. Sage, London Shearer E, Cho M, Magnus D (2020) Regulatory, social, ethical, and legal issues of artificial intelligence in medicine. In: Xing L, Giger ML, Min JK (eds) Artificial intelligence in medicine: technical basis and clinical applications. Acadamic Press, Cambridge, pp 457–477 Shenton AK (2004) Strategies for ensuring trustworthiness in qualitative research projects. Educ Inf 22:63–75 Shiraishi J, Li Q, Appelbaum D, Doi K (2011) Computer-aided diagnosis and artificial intelligence in clinical imaging. Semin Nucl Med 41(6):449–462 Sixsmith A, Horst BR, Simeonov D, Mihailidis A (2022) Older people’s use of digital technology during the COVID-19 pandemic. Bull Sci Technol Soc 42(1–2):19–24 Snyder J (2020) 31 Kennedy institute of ethics journal exploiting hope: how the promise of new medical interventions sustains us—and makes us vulnerable. Oxford University Press, New York Srivastava P, Hopwood N (2009) A practical iterative framework for qualitative data analysis. Int J Qual Methods 8(1):76–84 Tavanapong W et al (2022) Artificial intelligence for colonoscopy: past, present, and future. IEEE J Biomed Health Inform 3160098:1–17 Tong A, Sainsbury P, Craig J (2007) Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care 19(6):349–357 Topol E (2015) The patient will see you now: the future of medicine is in your hands. Basic Books, NY Topol E (2019) Deep medicine—how artificial intelligence can make healthcare human again. Basic Books, NY Tyler NS et al (2020) An artificial intelligence decision support system for the management of type 1 diabetes. Nat Metab 2(7):612–619 Tysnes O-B, Storstein A (2017) Epidemiology of Parkinson’s disease. J Neural Transm 124(8):901–915 Villar JR et al (2015) Improving human activity recognition and its application in early stroke diagnosis. Int J Neural Syst 25(4):1450036 Yu KH, Beam AL, Kohane IS (2018) Artificial intelligence in healthcare. Nat Biomed Eng 2(10):719–731