Artificial Intelligence (AI) refers to the imitation of human intelligence by machines. It is one of the fastest-growing technology areas nowadays. It is used in various sectors and industries, including defense, education, business, finance, and healthcare. The implementation of AI-related solutions in medicine is increasing at a significant rate. According to Buch et al. (2018), healthcare artificial intelligence projects recorded more investment than AI projects in other industries of the global economy in 2016. This paper seeks to expound on how new AI advancements can enable the medical field to attain greater levels of opportunity.
History of AI
It is imperative to acknowledge that artificial intelligence was formally introduced to the world in 1956. However, during the 1950s, there were mathematicians and scientists with the concept of AI in their minds. Alan Turing was one of them and highly contributed to the development of artificial intelligence. The individual published a paper in which he talked about the probability of developing machines that imitate human thinking. He speculated that machines could use available info to make decisions just like humans. Nonetheless, John Mccarthy introduced the first AI program in 1956. It was presented at a workshop known as the Dartmouth Summer Research Project on Artificial Intelligence (Ismail et al., 2019). People that attended became leaders of AI research for a while. However, interests in AI increased in the 1980s and 1990s. Many goals of artificial intelligence had been achieved by the first decade of the 21st century. For example, Gary Kasparov, a former world chess champion, was defeated by a chess-playing computer program in 1997. The occurrence contributed to the development of an AI decision-making program. Speech recognition software was also created in the same year. Today, artificial intelligence is used in almost all sectors. Companies like Amazon and Tesla use AI to make their products. Cogito, Alexa, and Siri also depict the application of artificial intelligence in the contemporary world.
Benefits of AI
Minimal Errors
Notably, the application of AI in the field of medicine has many benefits. Initially, AI machines have lower error rates as compared to humans. For example, they improve medication safety significantly. Artificial intelligence can assess large sets of data against dynamically changing and multifactorial criteria (Chan et al., 2018). Such enables it to decrease therapeutic and diagnostic errors. For example, an AI screening system can generate alerts that could otherwise be missed by humans. Therefore, artificial intelligence helps in minimizing errors in the medical field. In like manner, AI consists of machine learning algorithms that enable physicians to make better decisions. The machines outperform human doctors in the prediction of particular medical outcomes like the length of stay. It is imperative to acknowledge that humans are prone to errors. Physicians are no exception and can make medical errors like the wrong prediction about the most appropriate treatment for ICU patients. On the other hand, machine learning can help their human counterparts make better predictions about the effect of particular medications. Therefore, it is beyond a reasonable doubt that AI can minimize errors in the medical field.
Accuracy, Precision, and Speed
AI has been used in the medical field for a long time, and its benefits continue to evolve and grow with its capability to improve medical care and research. In line with this statement, machine learning algorithms help in increasing precision in medicine. AI machines can learn and improve without being explicitly coded by the programmer. In other words, machine learning enables them to learn and upgrade through experiences. Logistic regression and deep learning connote some of the machine learning algorithms used in medicine. They enable AI machines to retrieve data and learn for themselves. Such helps in increasing precision in medicine.
It is beyond a reasonable doubt that artificial intelligence can outperform humans in some tasks due to speed. For example, AI can be fast in medical imaging than physicians. As earlier, mentioned AI consists of machine learning and thus can learn from previous imaging scenarios and consequently analyze things that humans cannot detect. As such, AI helps detect other abnormalities that doctors may have missed, thus leading to accuracy (Das et al., 2018). From a liberal point of view, many medical entities and professionals will adopt AI medical imaging due to its ability to outperform humans in speed and accuracy. Through increasing accuracy, AI also reduces the costs of medication-related errors. For instance, AI highly contributes to the reduction of dosage errors in the medical field. AI can also make treatments more accessible and affordable to patients that cannot receive treatments due to high cost. Therefore, artificial intelligence increases precision, accuracy, and speed in the medical field, translating to other benefits such as cost-saving.
Susceptibility to Hostile Environments
Artificial intelligence is not affected by hostile environments. Human beings have succeeded in numerous ways. However, they are still extremely limited and fragile. Humans developed technologies to help in dealing with the challenges of hostile environments. However, AI can have a lower error rate than human beings if coded properly. As a result, they would have far-fetched speed, accuracy, and precision that would make them effective even in hostile environments. They would be able to perform dangerous tasks that humans cannot handle. They can endure problems that could hurt people. AI machines with properly fitted predefined algorithms can be used to perform tasks that cannot be done by humans. Therefore, artificial intelligence would bring numerous benefits in the medical field as it is not susceptible to hostile environments.
Problems Associated with the Medical Field
Lack of Workers
Inadequate staff is a critical problem in the medical profession all over the world. That said, AI would help in addressing the problem. For example, advancement in AI has led to the use of machines to diagnose patients. The action streamlines the daily duties of a physician, thus minimizing the impacts of staff shortage. AI medical imaging will also minimize radiologist's workloads. Artificial intelligence will need computerized assistants that can enter medical information according to a patient's conversation with doctors. Such will help address the impact of inadequate staffing as the technology will assist physicians in automating medical records. Artificial intelligence can also be used to analyze blood tests, endoscopic images, and resonance scans. Such minimizes the overload that occurs as a result of staff shortage. Therefore, using AI for everything from administration tasks to help with surgery can minimize the impacts of inadequate staff in the medical profession.
Long Working Hours
From a liberal point of view, inadequate staffing in the medical field forces medical professionals to work for long hours. Managers think that this helps in minimizing the impacts of staff shortage. However, working for long hours can lead to employee burnout, contributing to high absenteeism and turnover rates. Today, there is an increase in the number of chronic patients, and thus physicians may receive more data than they can analyze. Such compels them to work for long hours in an attempt to attend to the increasing number of patients. However, artificial intelligence can help in addressing this problem (Martin, 2019). The technology can help doctors minimize the time to spend on keyboards keying in patient information. AI can capture information automatically and, at the same time, make sure it is stored in the right and safe place. Such prevents doctors from working for long hours because the machines help them tackle some tasks.
High Costs for Advanced Degrees
It is imperative to acknowledge that tertiary education is expensive. As a result, most students tend to apply for student loans to cater to their financial needs in college. Such explains why most of them live in debt. Medical learners are no exception because their tuition cost is very high. However, AI can help in addressing this problem. Artificial intelligence can enable medical schools to automate administrative tasks and grading tasks. AI can also allow instructors to create an electronic curriculum that allows students to learn at home. Such will minimize the costs of pursuing advanced degrees.
AI in Practice and Future Decisions
Current Practices being implemented and Studied
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The Applications of AI in the Medical Field |
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Checking in health clinics |
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Decision support |
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Robotic surgery |
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Laboratory diagnosis |
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Precision medicine |
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Suggestion of treatment |
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Psychiatry |
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AI is already in play in the field of medicine. For example, patients check in health clinics through their computers and phones, appointments are being scheduled online, and health records are digitized. Such technologies are examples of AI and have transformed how people seek medical care. AI is being used for decision support, robotic surgery, and laboratory information system. For example, DXplain connotes an AI system that comes up with possible diagnoses (Kamensky, 2020). Such help physicians in making the best decision.
On the other hand, the da Vinci robotic surgical system is used in operating rooms. It has magnetized vision, precise movement, and robotic arms that enable doctors with precision in surgery that would have been impossible when operating manually. Germwatcher is another AI developed to track, detect, and investigate infections among hospitalized patients. Doctors are also providing online therapy for people with social anxiety. In the rear, Kardia signifies another AI that helps detect atrial fibrillation (Briganti & Le Moine, 2020). Therefore, artificial intelligence has numerous applications in medicine. Medical professionals are currently using AI in the form of computer techniques to suggest treatments and carry out diagnoses. AI plays a pivotal role in detecting meaningful relationships in a dataset. It is highly used in various medical situations to evaluate, treat, and predict medical outcomes.
Artificial intelligence is being tested and implemented in medicine for different treatments and dosing drugs in patients. The focus on AI in the field of radiology is inclining. In line with this statement, it is still being studied to diagnose and detect ailments in patients through magnetic resonance imaging and computerized tomography. The use of AI systems to detect cancer more articulately is still under research. Similarly, the application of artificial intelligence in psychiatry is still being studied. Therefore, various areas of AI in medicine are still under research.
Discussions health about AIs for the Future
Compelling evidence has shown that AI will dominate the future world. As such, the medical profession will undergo evolution due to the increased use of artificial intelligence systems. However, the technology will support medical professionals and not replace them. Machines cannot show compassion and empathy to patients. Therefore, patients will require physicians even in the event of extreme applications of AI. The machines will leave the responsibility for patient management to human physicians. However, they will guide patient management by extracting data from a patient's electronic record. Moreover, as machines help list possible diagnoses, the doctors will focus on interpreting the signals. Therefore, artificial intelligence will support medical professionals and not replace them. Concurrently, individuals considering joining the medical field in the future should have the willingness to learn, adapt, and grow alongside technological advancements because the profession is headed for evolution.
AI systems will be more advanced in the future and thus will be given more responsibility. For example, artificial intelligence systems could determine the commencement of static among type 2 diabetes' patients depending on the patient's history instead of following one algorithm for all patients. The technology will also be vital in preventive medicine in the future as it monitors large data sets. It will also perform medical tasks within a short time. As articulated by Haleem et al. (2019), AI will also be used for financial management in medicine. In the rear, AI will also be vital for digital supervision to enhance patient care.
Conclusion
To sum up, the application of artificial intelligence in medicine has various benefits. AI involves machines programmed to simulate the actions of humans. It minimizes errors by increasing accuracy and precision. It helps physicians make better decisions and predictions about the effect of particular medications. It is also essential in detecting other abnormalities that doctors may have missed. Moreover, AI systems are not vulnerable to hostile environments. Artificial intelligence can help in addressing common problems in the medical profession. It can minimize the impact of staff shortage and work for long hours. On the other hand, AI is used in various areas of medicine. It is used in surgery, decision making, and laboratory information systems. Other applications of medical AI are being studied. It is beyond a reasonable doubt that advancements in AI will enable the medical field to achieve greater levels of opportunities. AI systems will be more advanced in the future and thus will be given more responsibility. However, it is essential to acknowledge that artificial intelligence will not replace physicians but will rather support them. People considering joining the medical field in the future should have the inclination to learn, adapt, and grow alongside technological advancements because the profession is headed for evolution.
References
Briganti, G., & Le Moine, O. (2020). Artificial intelligence in medicine: Today and tomorrow. Frontiers in Medicine, 7, 27.
Buch, V. H., Ahmed, I., & Maruthappu, M. (2018). Artificial intelligence in medicine: current trends and future possibilities. Br J Gen Pract, 68(668), 143-144.
Chan, Y. K., Chen, Y. F., Pham, T., Chang, W., & Hsieh, M. Y. (2018). Artificial intelligence in medical applications. Journal of healthcare engineering, 2018.
Das, S., Biswas, S., Paul, A., & Dey, A. (2018). AI doctor: an intelligent approach for medical diagnosis. In Industry Interactive Innovations in Science, Engineering, and Technology (pp. 173-183). Springer, Singapore.
Haleem, A., Javaid, M., & Khan, I. H. (2019). Current status and applications of artificial intelligence (AI) in the medical field: an overview. Current Medicine Research and Practice, 9(6), 231-237.
Ismail, F., al Hosaini, A. A. H., Chan, S. W., Ruslan, R., & Bahrolsaini, K. M. (2019). Artificial Intelligence (AI).
Kamensky, S. (2020). Artificial Intelligence and Technology in Health Care: Overview and Possible Legal Implications. DePaul Journal of Health Care Law, 21(3), 3.
Martin, A. (2019). Using AI and NLP to Alleviate Physician Burnout.
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