AI and Medicine
Summary and conclusion
First is a summary of the numerous ways in which AI could be incorporated into the Healthcare system. As well as the likelihood and prioritization of its use in medicine according to the success criteria outlined earlier (capability, practicality, affordability and ethicality). AI algorithms are on the verge of being used to analyse medical images such as X-rays, MRI scans, and CT scans (Shelmerdine,2022) as well as ultrasound scans to detect abnormalities and diagnose diseases. This technology exists today and is very close to the efficacy required for clinical use. It is easily incorporated into existing imaging technology and can be used at scale relatively quickly. It has ethical implications, however, that will need to be addressed as the technology is brought into wide-scale use, most likely with modified versions of the regulations in place for other medical technologies already in use. AI can be used to accelerate the drug discovery process by identifying promising drug candidates and predicting their efficacy and safety. This is highly efficient and is very desirable for pharmaceutical companies as a large amount of the work required to identify and test new drugs is very repetitive and time-consuming. This could allow pharmaceutical scientists the opportunity to undertake more engaging and necessary roles (Gupta, 2021). AI can help personalize treatment plans based on a patient's unique characteristics. It can also enable remote patient monitoring by analysing data from wearable devices and providing real-time feedback to healthcare providers. It can also provide personalized health recommendations and reminders so that you can monitor improvement in a patient’s health and engagement. This has a great deal of utility to both patients and medical professionals. AI can improve the efficiency and accuracy of electronic health records by automating tasks such as data entry and analysis. Even inputting such data into medical records in the first place can be made more efficient by the use of AI. This would likely still require ratification by a clinician before the information was uploaded and disseminated. I think it is very unlikely that AI will have much more than a minor role in surgery at any point in the near future. There is very little research being done into this field and what little there is, by most indications suggests that such developments would require a great deal of funding and interest which currently does not exist.
Technical, ethical and patient care considerations of AI
This dissertation has examined the potential applications of artificial intelligence (AI) in the future of medicine, accounting for ethical, technical, and patient care considerations. The findings suggest that AI has the potential to revolutionize healthcare by improving diagnosis, treatment, and patient outcomes. However, it is essential to address ethical concerns such as patient privacy, bias, and accountability in AI decision-making. Additionally, technical considerations such as data quality and interoperability must be addressed to ensure the effectiveness and reliability of AI systems. Finally, patient care considerations must remain at the forefront of AI development to ensure that patients receive safe and effective care that meets their needs and preferences.
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