Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges
<h3>Introduction</h3><p dir="ltr">Artificial Intelligence is in the phase of health care, with transformative innovations in diagnostics, personalized treatment, and operational efficiency. While having potential, critical challenges are apparent in areas of safety, trust...
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2025
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| _version_ | 1864513538642411520 |
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| author | Muhammad Mohsin Khan (22303366) |
| author2 | Noman Shah (22150363) Nissar Shaikh (11659441) Abdulnasser Thabet (17151103) Talal alrabayah (22303369) Sirajeddin Belkhair (17151106) |
| author2_role | author author author author author |
| author_facet | Muhammad Mohsin Khan (22303366) Noman Shah (22150363) Nissar Shaikh (11659441) Abdulnasser Thabet (17151103) Talal alrabayah (22303369) Sirajeddin Belkhair (17151106) |
| author_role | author |
| dc.creator.none.fl_str_mv | Muhammad Mohsin Khan (22303366) Noman Shah (22150363) Nissar Shaikh (11659441) Abdulnasser Thabet (17151103) Talal alrabayah (22303369) Sirajeddin Belkhair (17151106) |
| dc.date.none.fl_str_mv | 2025-02-02T06:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.ijmedinf.2024.105780 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Towards_secure_and_trusted_AI_in_healthcare_A_systematic_review_of_emerging_innovations_and_ethical_challenges/30197737 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Health sciences Health services and systems Information and computing sciences Artificial intelligence Artificial Intelligence (AI) Healthcare Trust Safety Ethics Explainability Transparency Patient safety |
| dc.title.none.fl_str_mv | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <h3>Introduction</h3><p dir="ltr">Artificial Intelligence is in the phase of health care, with transformative innovations in diagnostics, personalized treatment, and operational efficiency. While having potential, critical challenges are apparent in areas of safety, trust, security, and ethical governance. The development of these challenges is important for promoting the responsible adoption of AI technologies into healthcare systems. </p><h3>Methods</h3><p dir="ltr">This <u>systematic review</u> of studies published between 2010 and 2023 addressed the applications of AI in healthcare and their implications for safety, transparency, and ethics. A comprehensive search was performed in PubMed, IEEE Xplore, Scopus, and Google Scholar. Those studies that met the inclusion criteria provided empirical evidence, theoretical insights, or systematic evaluations addressing trust, security, and ethical considerations. </p><h3>Results</h3><p dir="ltr">The analysis brought out both the innovative technologies and the continued challenges. Explainable AI (XAI) emerged as one of the significant developments. It made it possible for healthcare professionals to understand AI-driven recommendations, by this means increasing transparency and trust. Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. According to several studies, more than 60 % of healthcare professionals have expressed their hesitation in adopting AI systems due to a lack of transparency and fear of data insecurity. Moreover, the 2024 WotNot data breach uncovered weaknesses in AI technologies and highlighted the dire requirement for robust cybersecurity. </p><h3>Discussion</h3><p dir="ltr">Full understanding of the potential of AI will be possible only with putting into practice of ethical and technical maintains in healthcare systems. Effective strategies would include integrating bias mitigation methods, strengthening cybersecurity protocols to prevent breaches. Also by adopting interdisciplinary collaboration with the goal of forming transparent regulatory guidelines. These are very important steps toward earning trust and ensuring that AI systems are safe, reliable, and fair. </p><h3>Conclusion</h3><p dir="ltr">AI can bring transformative opportunities to improve healthcare outcomes, but successful implementation will depend on overcoming the challenges of trust, security, and ethics. Future research should focus on testing these technologies in multiple real-world settings, enhance their scalability, and fine-tune regulations to facilitate accountability. Only by combining technological innovations with ethical principles and strong governance can AI reshape healthcare, ensuring at the same time safety and trustworthiness.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Medical Informatics<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijmedinf.2024.105780" target="_blank">https://dx.doi.org/10.1016/j.ijmedinf.2024.105780</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_9e7967f15e7e4c119fbb1a2b58e9974c |
| identifier_str_mv | 10.1016/j.ijmedinf.2024.105780 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/30197737 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challengesMuhammad Mohsin Khan (22303366)Noman Shah (22150363)Nissar Shaikh (11659441)Abdulnasser Thabet (17151103)Talal alrabayah (22303369)Sirajeddin Belkhair (17151106)Health sciencesHealth services and systemsInformation and computing sciencesArtificial intelligenceArtificial Intelligence (AI)HealthcareTrustSafetyEthicsExplainabilityTransparencyPatient safety<h3>Introduction</h3><p dir="ltr">Artificial Intelligence is in the phase of health care, with transformative innovations in diagnostics, personalized treatment, and operational efficiency. While having potential, critical challenges are apparent in areas of safety, trust, security, and ethical governance. The development of these challenges is important for promoting the responsible adoption of AI technologies into healthcare systems. </p><h3>Methods</h3><p dir="ltr">This <u>systematic review</u> of studies published between 2010 and 2023 addressed the applications of AI in healthcare and their implications for safety, transparency, and ethics. A comprehensive search was performed in PubMed, IEEE Xplore, Scopus, and Google Scholar. Those studies that met the inclusion criteria provided empirical evidence, theoretical insights, or systematic evaluations addressing trust, security, and ethical considerations. </p><h3>Results</h3><p dir="ltr">The analysis brought out both the innovative technologies and the continued challenges. Explainable AI (XAI) emerged as one of the significant developments. It made it possible for healthcare professionals to understand AI-driven recommendations, by this means increasing transparency and trust. Still, challenges in adversarial attacks, algorithmic bias, and variable regulatory frameworks remain strong. According to several studies, more than 60 % of healthcare professionals have expressed their hesitation in adopting AI systems due to a lack of transparency and fear of data insecurity. Moreover, the 2024 WotNot data breach uncovered weaknesses in AI technologies and highlighted the dire requirement for robust cybersecurity. </p><h3>Discussion</h3><p dir="ltr">Full understanding of the potential of AI will be possible only with putting into practice of ethical and technical maintains in healthcare systems. Effective strategies would include integrating bias mitigation methods, strengthening cybersecurity protocols to prevent breaches. Also by adopting interdisciplinary collaboration with the goal of forming transparent regulatory guidelines. These are very important steps toward earning trust and ensuring that AI systems are safe, reliable, and fair. </p><h3>Conclusion</h3><p dir="ltr">AI can bring transformative opportunities to improve healthcare outcomes, but successful implementation will depend on overcoming the challenges of trust, security, and ethics. Future research should focus on testing these technologies in multiple real-world settings, enhance their scalability, and fine-tune regulations to facilitate accountability. Only by combining technological innovations with ethical principles and strong governance can AI reshape healthcare, ensuring at the same time safety and trustworthiness.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Medical Informatics<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijmedinf.2024.105780" target="_blank">https://dx.doi.org/10.1016/j.ijmedinf.2024.105780</a></p>2025-02-02T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.ijmedinf.2024.105780https://figshare.com/articles/journal_contribution/Towards_secure_and_trusted_AI_in_healthcare_A_systematic_review_of_emerging_innovations_and_ethical_challenges/30197737CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/301977372025-02-02T06:00:00Z |
| spellingShingle | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges Muhammad Mohsin Khan (22303366) Health sciences Health services and systems Information and computing sciences Artificial intelligence Artificial Intelligence (AI) Healthcare Trust Safety Ethics Explainability Transparency Patient safety |
| status_str | publishedVersion |
| title | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| title_full | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| title_fullStr | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| title_full_unstemmed | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| title_short | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| title_sort | Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges |
| topic | Health sciences Health services and systems Information and computing sciences Artificial intelligence Artificial Intelligence (AI) Healthcare Trust Safety Ethics Explainability Transparency Patient safety |