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The Role Of Artificial Intelligence In Medicine

Developments in the field of artificial intelligence (AI) has revolutionized the present day workplace. The medical sector does not lag behind. Artificial intelligence in healthcare has turned into a hot topic in recent years. Although AI in medicine has shown great potential and has been an added advantage in providing plenty of medical facilities with ease, there still exists concerns about losing the human touch [1] . Medicine being a people-focused profession, use of artificial intelligence in it can create few situations which would require manual intervention.

Read on to know in detail about how AI is being used in the healthcare sector today and the future of AI.

What Is Artificial Intelligence In Medicine?

Artificial intelligence in medicine is the use of artificial intelligence technology along with automated processes in the diagnosis and treatment of patients with ailments [2] . Several background steps form the basis of successful diagnosis and treatment. Some of these are as follows [3] :

  • Gathering data through tests and interviews with patients
  • Processing and analyzing results
  • Using various data sources to reach a conclusive diagnosis
  • Determining a treatment plan
  • Administering the chosen treatment method
  • Patient monitoring
  • Follow-up appointments

Most of the above-mentioned steps can be performed through automation. The idea behind making these background steps automated is that it can keep the medical professional free to take up other manual tasks. Also, automation ensures that tasks are completed more quickly. Automation facilitates more valuable use of human resources [4] .

In a study conducted in 2016, physicians spent more time on data entry and desk work than with patients [5] . The doctor-patient time is central to the medical profession which should not be taken up by administrative tasks. The primary task that many institutes focused on was to automate areas which can free up the time and effort of physicians. The goal should be the creation of balance between effective use of AI-oriented technology and the human strengths and judgement [6] .

How Is Artificial Intelligence Used In Medicine?

Artificial intelligence has already automated plenty of tasks in medicine. For instance, medical records being digitized, scheduling appointments online, patient check-in to hospitals through mobile phones, etc., - the technology usage seems to have increased in all walks of life.

Below mentioned are some examples that show the massive use of AI in medicine today [7] :

  • Robotic surgical systems [8] : A system that has robotic arms, magnetized vision and precise movement. This allows doctors to perform precision surgery.
  • AI therapy [9] : A course for people suffering from social anxiety.
  • Reduction of human error : Online application for patients to book appointments and routine tests. People can now consult a doctor online alongside checking symptoms, monitoring their health and ordering test kits.
  • Decision support systems [10] : When a set of symptoms are entered, a list of possible diagnosis is revealed.
  • Laboratory information systems [11] : A system is designed to detect, track and investigate infections when patients are hospitalized.

Use of artificial intelligence in the healthcare sector provides ample benefits such as reduction of manual tasks and freeing up the medical professional's time alongside increasing productivity and efficiency. But, above all, one of the main areas that have promoted the use of AI in medicine is the move that has been made towards 'precision medicine' [12] .

Experts believe that AI would make healthcare specialists move from conventional, one-size-fits-all medical solutions towards targeted treatments that are personalized therapies having unique drugs. With the presence of analyzed data, personalized treatment based on specific knowledge is easily feasible.

Common Applications Of Artificial Intelligence In Healthcare

The following are the most common ways by which AI is changing the healthcare sector currently and will continue to do so in the future.

1. Doing repetitive jobs [13]

Analyzing tests, CT scans, X-rays, data entry can be done quickly and more accurately with the help of robots. Radiology and cardiology are two areas where data analysis is extremely time-consuming.

2. Managing medical records

Compilation of information such as medical records and past history is one of the first steps in health care. The most widely used application of AI is data management. Digital automation plays an important role in this. The robots are designed to collect, store, re-format and trace data to provide consistent and quicker access [14] .

3. Digital consultation [15]

Medical consultation is being provided by doctors based on personal medical history and common medical knowledge. The features are available in the form of a mobile application. The users can feed in their symptoms. A recommended action is then provided based on the user's medical history.

4. Treatment design

Data obtained from a patient's file along with external research and clinical expertise are analyzed. This helps in selecting a customized treatment path [16] .

5. Medication management [17]

The use of medication by a patient can be monitored. A smartphone's webcam is used for this purpose. The phone is partnered with artificial intelligence to confirm that the patients are taking their prescriptions.

6. Virtual nurses [18]

Digital nurses are used to help people monitor a patient's condition. This also helps with follow-up treatments. This program uses machine learning to support patients.

7. Drug creation

Clinical trials for pharmaceuticals might take decades and are expensive too. This process could be made faster and cheaper with the use of artificial intelligence [19] .

8. Precision medicine

Cancer and vascular diseases can be detected early through body scans that are AI enabled [20] . Various tools (algorithm-enabled tools used for analysis of genomes) are used to search for mutations and links to diseases present in the DNA. Precision medicine could help in the early prediction of health issues that might be linked to genetics.

9. Health monitoring

The modern wearable health trackers [21] are capable of monitoring activity levels and heart rate. Alerts can be sent to the person to get more exercise. Such applications also allow sharing the information with doctors to obtain additional points on the habits of the patient.

10. Healthcare system analysis [22]

Systems are being created that can digitally glance through the data and highlight mistakes in treatment, inefficiencies in the workflow or in cases where unnecessary patient hospitalization is suggested.

Artificial Intelligence In The Future

With more studies being conducted on the future of AI and automation, various possibilities and arguments tend to arise, especially with crucial sectors such as medicine. The general idea that most researchers agree on is that routine tasks such as data collection or entry are fine to be taken care of by machines, however, the requirement for a human role does not change as every machine-done thing needs to be ultimately monitored and controlled. Aspects like judgement, creativity and empathy are possible only by humans, and not machines [23] .

Nevertheless, it is well-accepted that there is no doubt that the use of AI increases efficiency, pairing humans and AI would improve the human's professional performance drastically too [24] . The future of medical science strongly relies on the creation of hybrid models that pair humans and machines together [25] .

It is understood that it is unlikely that machines will replace the need for human doctors in the near future. However, people considering the medical profession should accept that they would need to adapt, learn and grow alongside technological advancements especially with respect to artificial intelligence.

View Article References
  1. [1] Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H., … Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future.Stroke and vascular neurology,2(4), 230-243.
  2. [2] Guo, J., & Li, B. (2018). The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries.Health equity,2(1), 174-181.
  3. [3] Hall M. (2018). Artificial intelligence and nuclear medicine.Nuclear medicine communications,40(1), 1-2.
  4. [4] Tang, X., Wang, B., & Rong, Y. (2018). Artificial intelligence will reduce the need for clinical medical physicists.Journal of applied clinical medical physics,19(1), 6-9.
  5. [5] Konrad, T. R., Link, C. L., Shackelton, R. J., Marceau, L. D., von dem Knesebeck, O., Siegrist, J., Arber, S., Adams, A., … McKinlay, J. B. (2010). It's about time: physicians' perceptions of time constraints in primary care medical practice in three national healthcare systems.Medical care,48(2), 95-100.
  6. [6] Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing Machine Learning in Health Care - Addressing Ethical Challenges.The New England journal of medicine,378(11), 981-983.
  7. [7] Craft J. A. (2018). Artificial Intelligence and the Softer Side of Medicine.Missouri medicine,115(5), 406-409.
  8. [8] Leung, T., & Vyas, D. (2014). Robotic Surgery: Applications.American journal of robotic surgery,1(1), 1-64.
  9. [9] D'Alfonso, S., Santesteban-Echarri, O., Rice, S., Wadley, G., Lederman, R., Miles, C., Gleeson, J., … Alvarez-Jimenez, M. (2017). Artificial Intelligence-Assisted Online Social Therapy for Youth Mental Health.Frontiers in psychology,8, 796.
  10. [10] Castaneda, C., Nalley, K., Mannion, C., Bhattacharyya, P., Blake, P., Pecora, A., Goy, A., … Suh, K. S. (2015). Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine.Journal of clinical bioinformatics,5, 4.
  11. [11] Mathews, A., & Marc, D. (2017). Usability Evaluation of Laboratory Information Systems.Journal of pathology informatics,8, 40.
  12. [12] Fröhlich, H., Balling, R., Beerenwinkel, N., Kohlbacher, O., Kumar, S., Lengauer, T., Maathuis, M. H., Moreau, Y., Murphy, S. A., Przytycka, T. M., Rebhan, M., Röst, H., Schuppert, A., Schwab, M., Spang, R., Stekhoven, D., Sun, J., Weber, A., Ziemek, D., … Zupan, B. (2018). From hype to reality: data science enabling personalized medicine.BMC medicine,16(1), 150.
  13. [13] Meskó, B., Hetényi, G., & Győrffy, Z. (2018). Will artificial intelligence solve the human resource crisis in healthcare?.BMC health services research,18(1), 545.
  14. [14] Bui, K. D., & Johnson, M. J. (2018). Designing robot-assisted neurorehabilitation strategies for people with both HIV and stroke.Journal of neuroengineering and rehabilitation,15(1), 75.
  15. [15] Santana, S., Lausen, B., Bujnowska-Fedak, M., Chronaki, C., Kummervold, P. E., Rasmussen, J., & Sorensen, T. (2010). Online communication between doctors and patients in Europe: status and perspectives.Journal of medical Internet research,12(2), e20.
  16. [16] Kaur, J. S., & Petereit, D. G. (2012). Personalized medicine: challenge and promise.Journal of cancer education : the official journal of the American Association for Cancer Education,27(1 Suppl), S12-17.
  17. [17] Labovitz, D. L., Shafner, L., Reyes Gil, M., Virmani, D., & Hanina, A. (2017). Using Artificial Intelligence to Reduce the Risk of Nonadherence in Patients on Anticoagulation Therapy.Stroke,48(5), 1416-1419.
  18. [18] Darvish, A., Bahramnezhad, F., Keyhanian, S., & Navidhamidi, M. (2014). The role of nursing informatics on promoting quality of health care and the need for appropriate education.Global journal of health science,6(6), 11-18.
  19. [19] Hessler, G., & Baringhaus, K. H. (2018). Artificial Intelligence in Drug Design.Molecules (Basel, Switzerland),23(10), 2520.
  20. [20] Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. (2018). Artificial intelligence in radiology.Nature reviews. Cancer,18(8), 500-510.
  21. [21] Maher, C., Ryan, J., Ambrosi, C., & Edney, S. (2017). Users' experiences of wearable activity trackers: a cross-sectional study.BMC public health,17(1), 880.
  22. [22] Panch, T., Szolovits, P., & Atun, R. (2018). Artificial intelligence, machine learning and health systems.Journal of global health,8(2), 020303.
  23. [23] Patel, V. L., Shortliffe, E. H., Stefanelli, M., Szolovits, P., Berthold, M. R., Bellazzi, R., & Abu-Hanna, A. (2008). The coming of age of artificial intelligence in medicine.Artificial intelligence in medicine,46(1), 5-17.
  24. [24] Jones, L. D., Golan, D., Hanna, S. A., & Ramachandran, M. (2018). Artificial intelligence, machine learning and the evolution of healthcare: A bright future or cause for concern?.Bone & joint research,7(3), 223-225.
  25. [25] Tacchella, A., Romano, S., Ferraldeschi, M., Salvetti, M., Zaccaria, A., Crisanti, A., & Grassi, F. (2018). Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study.F1000Research,6, 2172.
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