AI in Biomedical Engineering by Abhiram Bandi, Austin, Texas
The role of Artificial Intelligence (AI) in biomedical engineering is such a significant idea in the world of medicine. From January 2012 all the way to June 2018 the usage of AI assisted surgery or robotic surgery increased by an immense 13.3%. During the Covid-19 pandemic, the use of AI has been even more prevalent and thus causing more than 56% of health executives to have a more in depth understanding of the implementation of AI in the world of medicine. AI in medicine can be both a good and bad thing, because humans are humans and AI is, of course, an AI.
In the late 1900s, an individual named Alan Turing, a renaissance man, investigated the prospect of AI. He stated that machines and humans are similar, so if humans can have the capability of a problem-solving mindset, why couldn’t machines. In 1950 he released a paper called “Computing Machinery and Intelligence”, in which he talked about the possibility of what we know today as AI. AI is revolutionizing the world of healthcare and medicine in ways you cannot possibly imagine, from robots assisting in surgery to AI tools that can screen patients for vision loss. AI provides so much to the table for surgeons, and can also diagnose problems, have faster documentation of patient files and previous illnesses, and analyze data faster than ever.
AI in healthcare is amazing but it also provides risks because at the end of the day a computer cannot tell the difference between right and wrong or more painful and less painful. AI will not always be right, and sometimes will compromise the safety of a patient with a wrong diagnosis. A 2018 survey of 500 people revealed that only 35 percent of the people were comfortable with their data being safely stored, which brings up a question of privacy. What if a hacker got ahold of the patient's private information through the AI? First the patient’s privacy is gone therefore decreasing the trust in the computer, second who is to blame for the loss of privacy? The AI? Or the hospital who accepted the AI being there? If the AI system recommends the wrong drug or does not catch a tumor in a scan , it could put the patient at risk. If an AI system made a mistake it would not bode well for the patient's family and people will start hearing about why AI should not be used in hospitals. Another problem is data availability because getting all the patient data is not as easy as it sounds. Patients usually switch providers or try to find other insurance companies making it harder for the AI to process so much data accurately. Professional realignment is something future doctors and healthcare professionals will have to worry about. Professional realignment in healthcare is when AI takes over some medical profession such as radiology because it is very easy for a machine to do. This is bad because over time doctors' knowledge will decrease and they will not catch the mistakes the AI makes.
Is AI in healthcare worth the risks? Does the good outweigh the bad? In short, yes. AI in the medical field is absolutely revolutionizing, because it helps healthcare professionals better understand the needs of the patients. One area where AI has shown much promise is deep learning to diagnose diseases, because an early accurate diagnosis can save a patient’s life. The AI processes information much faster than a human, so this can help the AI get a much more likely cause of the system, than the doctors. AI can change the way we look at everything, not just healthcare, from navigation apps to smart assistants such as Alexa and Siri, AI has the potential to do so much.
Bali, Jatinder, et al. “Artificial Intelligence (AI) in Healthcare and Biomedical Research: Why a Strong Computational/AI Bioethics Framework Is Required?” Indian Journal of Ophthalmology, Medknow Publications & Media Pvt Ltd, Jan. 2019, www.ncbi.nlm.nih.gov/pmc/articles/PMC6324122/.
Secinaro, Silvana, et al. “The Role of Artificial Intelligence in Healthcare: a Structured Literature Review.” BMC Medical Informatics and Decision Making, BioMed Central, 10 Apr. 2021, bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-021-01488-9.