Healthcare systems are complex and often siloed , making it difficult to integrate AI algorithms into existing workflows and processes .
AI ( XAI ), which aims to provide a deeper understanding of how AI algorithms arrive at their decisions , making the decision-making process more transparent and interpretable . By incorporating XAI techniques , clinicians and patients can gain insights into the reasoning behind AI-generated recommendations or predictions , fostering trust and facilitating the adoption of AI in healthcare .
Data privacy and security are also major challenges in the application of AI in healthcare . Healthcare data is sensitive and personal , and it is essential to ensure that it is protected and kept confidential . To overcome this challenge , it is important to have robust data security and privacy measures in place , such as encryption and secure data storage , to ensure that healthcare data is not misused or accessed by unauthorised parties . A study published in BMC Medical Ethics ( Murdoch , B ., 2021 ) addressed the access , use and control of patient data in private hands . Some recent public-private partnerships for implementing AI have resulted in poor protection of privacy . As such , there have been calls for greater systemic oversight of big data health research . Appropriate safeguards must be in place to maintain privacy and patient agency . Private custodians of data can be impacted by competing goals and should be structurally encouraged to ensure data protection and to deter alternative use thereof .
Another set of concerns relates to the external risk of privacy breaches through AI-driven methods . The ability to de-identify or anonymise patient health data may be compromised or even nullified considering new algorithms that have successfully reidentified such data . This could increase the risk to patient data under private custodianship . This highlights the need for regulations that emphasise patient agency and consent and should encourage increasingly sophisticated methods of data anonymisation and protection .
Another challenge in the application of AI in healthcare is ethical and legal considerations . AI algorithms can have unintended consequences
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