05 Oct How has clinical AI interconnected with an administrative function? What projects are being worked on that may be available in the near future? What are barriers that are currently preven

 Thomas

Artificial intelligence helps decrease the amount of time it takes to gather clinical information for clinical trials and collecting proof for a diagnosis (IBM). With the use of natural language processing, things such as unstructured data and plain text can be transformed into meaningful data that can not only be used to make better machine learning models but can also improve the accuracy and speed of clinical decisions and studies (Siwicki, 2022).  

      Improving and learning more about AI (Artificial Intelligence) to advance things such as medical image recognition and health equity are currently in the works and are improving at a fast rate. We might one day live in a world where it is standard practice for providers to use AI to verify their findings on X-rays and other scans and where there are minimal health disparities within studies.  

       Trusting and verifying the accuracy of machines stands as one of the biggest challenges when trying to develop AI in healthcare (IBM). The topic of AI sentience also stands as a very controversial topic that raises various questions such as whether or not algorithms can truly grant machines a will of their own and if that should even be a goal (Shah, 2022). The primary areas that limit the growth of AI stand as finances, research, willingness to advance, acceptance and trust.  

                                                                                 References 

IBM. (n.d.).  What is Artificial Intelligence in Healthcare? IBM. Retrieved October 4, 2022, from  https://www.ibm.com/topics/artificial-intelligence-healthcare Links to an external site.  

Shah, C. (2022, July 6).  Sentient ai? convincing you it's human is just part of LAMDA's job. Healthcare IT News. Retrieved October 4, 2022, from  https://www.healthcareitnews.com/blog/sentient-ai-convincing-you-it-s-human-just-part-lamda-s-job Links to an external site.  

Siwicki, B. (2022, July 11).  How ai and NLP can boost care via remote patient monitoring. Healthcare IT News. Retrieved October 4, 2022, from  https://www.healthcareitnews.com/news/how-ai-and-nlp-can-boost-care-remote-patient-monitoring?mkt_tok=NDIwLVlOQS0yOTIAAAGFkiRcQvSIW2f5zFgKTjUZH_Hw2bXEBVLrIKiVFHxxR2JLz8f27ZqNsHbBs0x3LztwgdCqalZtl1JkM45CXghZsgnM4npRQXIPcDFhwew Links to an external site.  

Angela(Reply to Thomas posting)

Thomas,

I agree with your comment on Ryan's post as well as the issues with trusting AI.  Not only is it controversial in terms of machine learning (threats of privacy problems, ethical concerns, and medical errors) but also patient/people care.  Thank you for your post.   

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Jenny

Clinical AI has connected to administrative function by assisting healthcare providers provide better quality care, better patient communication/satisfaction, and  storing/collecting/finding data more efficiently and timely. The IBM plans to "Improve efficiency and care, Deeper Insights with AI, and Beneficial Integration". A barrier that prevents more innovation is the sets regulations of safety and trust that the healthcare industry has especially when it comes to new/advanced AI into healthcare.

References:

What is Artificial Intelligence in Healthcare? IBM. (n.d.). Retrieved October 3, 2022, from https://www.ibm.com/topics/artificial-intelligence-healthcare

Angela(Reply to Jenny)

Jenny,

I believe the advancement of AI to be both extremely fascinating and concerning. There's no denying that the world of healthcare will improve with the use of AI, but what scares me the most is how far many people want to take it. I definitely appreciate the fact that there are rules and regulations for the implementation of AI!