f Digital Twins (Artificial Intelligence and Machine Learning) for Diagnosis of Alzheimer’s Disease: Ethical and Regulatory Aspects

References

1. PettiU. NyrupR. SkopekJ.M. KorhonenA. Ethical considerations in the early detection of Alzheimer’s disease using speech and AIFAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency12 June, pp. 1062–1075, 2023.10.1145/3593013.3594063
   [Google Scholar]
2. HineC. NilforooshanR. BarnaghiP. Ethical considerations in design and implementation of home-based smart care for dementia.Nurs. Ethics20222941035104610.1177/09697330211062980 35105196
   [Google Scholar]
3. UrsinF. TimmermannC. StegerF. Ethical implications of Alzheimer’s disease prediction in asymptomatic individuals through artificial intelligence.Diagnostics202111344010.3390/diagnostics11030440 33806501
   [Google Scholar]
4. MirkinS. AlbensiB.C. Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer’s disease?Front. Aging Neurosci.202315109423310.3389/fnagi.2023.1094233 37187577
   [Google Scholar]
5. IencaM. IgnatiadisK. Artificial intelligence in clinical neuroscience: methodological and ethical challenges.AJOB Neurosci.2020112778710.1080/21507740.2020.1740352 32228387
   [Google Scholar]
6. ReddyS. AllanS. CoghlanS. CooperP. A governance model for the application of AI in health care.J. Am. Med. Inform. Assoc.202027349149710.1093/jamia/ocz192 31682262
   [Google Scholar]
7. SimonD.A. EvansB.J. ShacharC. CohenI.G. Should Alexa diagnose Alzheimer’s?: Legal and ethical issues with at-home consumer devices.Cell Rep. Med.202231210069210.1016/j.xcrm.2022.100692 35882237
   [Google Scholar]
8. GaonkarB. CookK. MacyszynL. Ethical issues arising due to bias in training AI algorithms in healthcare and data sharing as a potential solution.AIEJ2020112
   [Google Scholar]
9. RefoloP. SacchiniD. Di BidinoR. PapaveroS.C. GoveD. TveterM. CicchettiA. HaraldsenI. The ethical relevance of explainability for AI-solutions for early diagnosis of dementia33rd Alzheimer Europe ConferenceHelsinki, 16-18 October2023
   [Google Scholar]
10. KellmeyerP. Ethical issues in the application of machine learning to brain disorders.Machine Learn.202032934210.1016/B978‑0‑12‑815739‑8.00018‑3
    [Google Scholar]
11. Operation Endgame’ Hits Malware Delivery PlatformsAvailable from: https://krebsonsecurity.com/2023/04/many-public-salesforce-sites-are-leaking-private-data/
12. MitrovskaA. SafariP. RitterK. ShariatiB. FischerJ.K. Secure federated learning for Alzheimer’s disease detection.Front. Aging Neurosci.202416132403210.3389/fnagi.2024.1324032 38515517
    [Google Scholar]
13. MeerzaS.I. LiZ. LiuL. ZhangJ. LiuJ. Fair and privacy-preserving alzheimer’s disease diagnosis based on spontaneous speech analysis via federated learning.Annu. Int. Conf. IEEE Eng. Med. Biol. Soc.vol. 2022, 2022pp. 1362-136510.1109/EMBC48229.2022.9871204
    [Google Scholar]
14. LeiB. ZhuY. LiangE. YangP. ChenS. HuH. XieH. WeiZ. HaoF. SongX. WangT. XiaoX. WangS. HanH. Federated domain adaptation via transformer for multi-site alzheimer’s disease diagnosis.IEEE Trans. Med. Imaging202342123651366410.1109/TMI.2023.3300725 37527297
    [Google Scholar]
15. CastroF. ImpedovoD. PirloG. A federated learning system with biometric medical image authentication for Alzheimer’s diagnosisProceedings of the 13th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2024)pp.951-960, 202410.5220/0012550200003654
    [Google Scholar]
16. QianC. XiongH. LiJ. FeDeFo: A personalized federated deep forest framework for alzheimer’s disease diagnosisProceedings of the 35th International Conference on Software Engineering and Knowledge Engineering (SEKE)pp. 572-577, 202310.18293/SEKE2023‑013
    [Google Scholar]