from a computer to conduct focused tasks , while deep learning uses premade algorithms modeled after human thinking , with the expectation that the computer will expand upon these to detect patterns and associations . 4
The term “ Artificial Intelligence ” has been around since the 1950s . 5 One of its first founders , Alan Turing invented the “ Turing test ,” which determined whether a human interrogator can differentiate between an AI computer or a human ’ s answer to certain questions . The success of the Turing test led to further developments and over time , the concept of AI evolved and began to be included in various other sectors . 5 General Motors developed the first industrial robot , “ Unimate ,” that powered manufacturing tasks like welding and metalworking processes . For a short period , AI production stagnated due to decreased interest and funding . This did not stop engineers and pioneers , whose collaborations continued to advance AI . In the modern era , AI has become a part of our day-to day life . Commonly used sites like Google and Facebook utilize AI to display posts about our interests based on previous search histories ; Netflix shows suggested movies / shows based on what we have watched before . All this big data is important to compartmentalize and understand our own interests and behaviors . As we began to watch how successful AI has evolved in the manufacturing and engineering world to our modern era , there ’ s been a large focus on using AI to improve patient care .
The introduction of Artificial Intelligence in Medicine ( AIM ) has spurred heavy interest in several stakeholders , with federal investment increasing over 50 % from 2018-2020 . Since 2010 , there ’ s been a large surge in investment from venture capital firms and others to finance new health care-based companies that promote the use of AIM . 7 Statistics show that the AIM market is rapidly growing and expected to have a 40 % compound annual rate , reaching $ 6.6 billion in 2021 . 7 Projections even show that by 2027 , the AIM market is expected to reach $ 67.4 billion . 8 The COVID-19 pandemic has accelerated the rate of acquisition of AIM leading to important initiatives like telemedicine and medical technology tackling COVID-19-related complications . Digital medicine and machine learning have broken down big data to formulate algorithms and networks to create a “ personalized ” progress chart for each patient , who can keep track on smart watches and phones . Providers and patients have promoted personalized medicine as an emerging method for proper patient care management , and AIM has strongly influenced it by increasing active patient participation . Despite all the benefits and expansion of AIM , some doctors and groups have been resistant to implementing it .
The future of medical implementation of artificial intelligence depends on whether the high costs drop , and whether the fear of “ replacing ” physicians with better diagnostic options will grow . Its rapid changes and expansion have contributed to this resistance against it . People fear that patient confidentiality will get breached . Improving care management using better programs should be a priority .
ARTIFICIAL INTELLIGENCE
It is important to work together with AIM , with humans and machines dominant in their skill sets , but ensuring human oversight of all . Pioneers developing AIM must work with clinicians from the start , optimizing the design for the user , not for the machine . Most AIM organizations have been led by entrepreneurs and engineers who have experience in developing solutions , but poor exposure to the real-life problems we deal with . This contributes to the distrust doctors have towards AIM and can explain the resistance to implementing in the hospital and clinic . 10
Medical schools should train medical students on the principles of AIM and how it might impact their medical practice in the future , using programs that teach students about the process of biomedical innovation , and how to optimize it to improve patient care management . We must teach the next generation of physicians about its rapid expansion , current issues and future benefits . It is important for our next generation of physicians to accept that medical technology will be involved in patient care and to focus on improving AIM to its fullest capacity to provide the best level of care to our patients .
References :
1 https :// observer . com / 2020 / 02 / siri-co-inventor-tom-gruber-internet-psychology-experiment /
2 https :// www . britannica . com / technology / artificial-intelligence
3 https :// link . springer . com / article / 10.1007 / s11673-020-10080-1
4 https :// link . springer . com / article / 10.1007 / s12525-021-00475-2
5 https :// www . giejournal . org / article / S0016-5107 ( 20 ) 34466-7 / fulltext
6 https :// www . mckinsey . com / industries / healthcare-systems-and-services / our-insights / transforming-healthcare-with-ai
7 https :// www . ncbi . nlm . nih . gov / pmc / articles / PMC7325854 /# bib4
8 https :// www . marketsandmarkets . com / Market-Reports / artificial-intelligence-healthcare-market-54679303 . html
9 https :// www . ncbi . nlm . nih . gov / pmc / articles / PMC6691444 /
10 https :// journals . sagepub . com / doi / full / 10.1177 / 23821205211036836
Ankur Gupta is a third-year medical student at the University of Louisville School of Medicine .
APRIL 2022 19