LATEST NEWS

International Journal of Modern Computation, Information and Communication Technology

ISSN 2581-5954

November 2018, Vol. 1, Issue 6, p. 103-110.​​

Artificial Intelligence in Healthcare – A Review 
N. Murali¹, N. Sivakumaran²*
¹International College of Business and Technology, Biomedical Science Department, No. 36, De Kretser Place, Bambalapitiya Colombo 04
²School of Science, Edulink International Campus, No 6, Glen Aber Place, Bambalapitiya, Colombo 04, Sri Lanka.
*Corresponding author’s e-mail:
snivethika25@gmail.com    

Abstract

Artificial intelligence (AI) is defined as a field of science and engineering concerned about the computational comprehension of what is commonly called intelligent behavior, and with the creation of artifacts that exhibit such behavior. It is the subfield of computer science. AI turning into a well known field in computer science as it has enhanced the human life in many areas. AI has recently surpassed human performance in several domains, and there is great hope that in healthcare. AI may allow for better prevention, detection, diagnosis, and treatment of disease. Major disease areas that use AI tool include cancer, neurology, cardiology and diabetes. Review contains the current status of AI applications in healthcare. AI can also be used to automatically spot problems and threats to patient safety, such as patterns of sub- optimal care or outbreaks of hospital-acquired illness with high accuracy and speed. A few ongoing researches of AI applications in healthcare that provide a view of a future where healthcare delivery is more unified, human experiences. This review will also explore how AI and machine learning can save lives by helping individual patients.

Keywords: Artificial Intelligence; Computer; Data; Diseases; Healthcare; Robots.

References

  1. ​Boden MA. Creativity and artificial intelligence. Artificial Intelligence 1998;103:347-56.
  2. Fogel AL, Kvedar JC. Artificial intelligence powers digital medicine. NPJ Digit Med 2018;1:5.
  3. Ranganath R, Gerrish S, Blei DM. Black Box Variational Inference. Aistats 2014;33:814-22.
  4. Spector L. Evolution of artificial intelligence.  Artificial Intelligence 2006;170:1251-53.
  5. Shulman C. How Hard is Artificial Intelligence ? Evolutionary Arguments and Selection Effects. Journals of Consciousness Studies 2012;19:1-23.
  6. Ramesh AN, Kambhampati C, Monson JRT, Drew PJ. Artificial intelligence in medicine. Ann R Coll Surg Engl  2004;44:334-8.
  7. Tomar D, Agarwal S. A survey on Data Mining approaches for Healthcare International Journal of Bioscience and Biotechnology 2013;5:241-66.
  8. Langen PA, Katz JS, Dempsey G, Pompano J. Remote monitoring of high-risk patients using artificial intelligence. United States Patent. 1993:1-13.
  9. Derrington D. Artificial Intelligence for Health and Health Care. Healthit.  2017;7508:65.
  10. Sensmeier J. Harnessing the Power of Artificial Intelligence. Nursing Management 2017;48:14-19.
  11. Hockstein NG, Gourin CG, Faust RA, Terris DJ. A history of robots: From science fiction to surgical robotics. J Robot Surg 2007;1:113-8.
  12. Wukkadada B, Saiswani VP. Online Healthcare System Using Cloud Computing and Artificial Intelligence. IOSR Journal of Computer Engineering 2000;20:S40-S3.
  13. Mohammadzadeh N, Safdari R. Artificial Intelligence Tools in Health Information Management. International Journal of Hospital Research 2012;1:71-6.
  14. Lieberman H, Mason C. Intelligent agent software for medicine. Stud Health Technol Inform 2002;08:99-109.
  15. Maglogiannis I. Introducing Intelligence in Electronic Healthcare Systems: State of the Art and Future Trends. Artificial Intelligence 1970:71-90.
  16. Mesko B. The role of artificial intelligence in precision medicine. Expert Rev Precis Med Drug Dev 2017;2:239-41.
  17. Chou S, Chang W, Cheng CY, Jehng JC, Chang C. An information retrieval system for medical records & documents. Int Conf IEEE Eng Med Biol Soc 2008:1474-7.
  18. Goldman LW. Principles of CT and CT Technology.  J Nucl Med Technol 2007;35:115-28.
  19. Filler A. The History, Development and Impact of Computed Imaging in Neurological Diagnosis and Neurosurgery: CT, MRI, and DTI. Nat Preced 2009:1-76.
  20. Salman M, Ahmed AW, Khan A, Raza B, Latif K. Artificial Intelligence in Bio-Medical Domain An Overview of AI Based Innovations in Medical. Int J Adv Comput Sci Appl 2017;8:319-27.
  21. Pacis DMM, Subido EDC, Bugtai NT. Trends in telemedicine utilizing artificial intelligence. AIP Conf Proc 1933:1-10.
  22. C. I. F. N. I. F. B. Digital healthcare s.l.  gpbullhound. 2013:91643080.
  23. Imison C, Castle-clarke S, Watson R, Edwards N. Delivering the benefits of digital health care. The Nuffield Trust 2016:1-108.
  24. Coiera E. Communication Systems in Healthcare. The Clinical Biochemist Review 2006;27:89-98.
  25. Cowie J. Evaluation of a Digital Consultation and Self-Care Advice Tool in Primary Care : A Multi-Methods Study. Int J Environ Res Public Health. 2018;15:E896
  26. Horner K, Wagner E, Tufano J. Electronic Consultations Between Primary and Speaciality Care Clinicians: Early Insights. The Commonwealth Fund. 2011;23:1-14.
  27. Svetlana I, Zorica D, Jelena P, Jelena P. Artificial intelligence in pharmaceutical product formulation : neural computing. Chemical Industry and Chemical Engineering Quarterly 2009;15:227-36.
  28. Agrawal P. Artificial Intelligence in Drug Discovery and Development. Journal of Pharmacovigilance 2018;6:1-2.
  29. Er O, Abakay A.  Use of artificial intelligence techniques for diagnosis of malignant pleural mesothelioma. Dicle Medical Journal 2015;42:5-11.
  30. Al-shamasneh ARM. Artificial Intelligence Techniques for Cancer Detection and Classification : Review Study.  European Scientific Journal 2017;13:342-70.
  31. Jaleel JA, Salim S, Aswin RB. Diagnosis and Detection of Skin Cancer Using Artificial Intelligence. International Journal of Engineering and Innovative Technology 2013;3:311-15.
  32. Sumathi MR, Poorna B, Prediction of Mental Health Problems Among Children Using Machine Learning Techniques. Int J Adv Comput Sci Appl 2016;7:552-7.
  33. Erguzel TT, Ozekes S. Artificial intelligence approaches in psychiatric disorders.  The Journal of Neurobehavioral Studies 2014;1:52-53.
  34. Luxton DD, Health. Artificial Intelligence in Psychological Practice : Current and Future Applications and Implications. Professional Psychology Research and Practice 2014;45:332-9.
  35. Ko BC. A Brief Review of Facial Emotion Recognition Based on Visual Information.  Sensors 2018;18:E401.
  36. Sreevatsan AN, Sathish Kumar KG, Rakeshsharma S, Roomi MM. Emotion recognition from facial expression-A target oriented approach using neural network Emotion Recognition from Facial Expressions : A Target Oriented Approach Using Neural Network. Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing, 2004:1-6.
  37. Boz H. Kose U. Emotion Extraction from Facial Expressions by Using Artificial Intelligence Techniques. Broad Research in Artificial Intelligence and Neuroscience 2017;8:5-16.
  38. Sg M, Ak T, St A, Sv S, Mj O.  Role of Artificial Intelligence in Health Care.  Biochemistry 2017;11:1-14.
  39. Montani S, Bellazzi R, Riva A, Larizza C, Portinale L, Stefanelli M. Artificial Intelligence Techniques for Diabetes Management : the T-IDDM Project. ECAI 2000:1-5.
  40. Buch V, Varughese G, Maruthappu M. Commentary Artificial intelligence in diabetes care.  Diabet Med 2018:35:495-7.
  41. Malanda UL, Bot SD, Nijpels G. Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients: It is time to face the evidence.  Diabetes Care 2013;36:176-8.
  42. Juza RM, Haluck RS, Pauli EM, Rogers AM, Lyn-sue JR. Robotic cholecystectomy : A cost comparison with historically novel laparoscopic cholecystectomy. OA Robot Surg 2014;2:1-4.
  43. Prabu AJ, Narmadha J, Jeyaprakash K. Artificial Intelligence Robotically Assisted Brain Surgery. IOSR Journal of Engineering 2014;4:9-14.
  44. Bodner J, Augustin F, Wykypiel H, Fish J, Muehlmann G, Wetscher G, Schmid T. The da Vinci robotic system for general surgical applications: A critical interim appraisal.  Swiss Med Wkly 2005;135:674-78.
  45. Technion T. An Autonomous Crawling Micro-Robot. The Technology Institute, Israel. 2008.
  46. Bishara MA. New Robotic Hair Transplantation Technology Provides Path to the Future ARTAS Hair Studio and ARTAS Robotic System Signal a Paradigm Shift in Hair Restoration. Asthetic guide.  2014:1-6.
  47. Piltan F, Emamzadeh S, Mirzaei M. PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB / SIMULINK and Their Integration into Graduate / Undergraduate Nonlinear Control, Robotics and MATLAB Courses.  Int J Robot Autom 2012;6:106-50.
  48. Camarillo DB, Krummel TM, Salisbury JK Jr. Robotic Technology in Surgery : Past, Present and Future. The American Journel of Surgery. 2004:188:2S-15S.
  49. Bluma AL, Langley P. Artificial Intelligence Selection of relevant features and examples in machine.  Artificial Intelligence 1997;97:245-271.
  50. Narula A, Narula NK, Khanna S, Narula R, Narula J, Narula A. Future Prospects of Artificial Intelligence in Robotics Software , A healthcare Perspective.  International Journal of Applied Engineering 2014;9:10271-80.
  51. Berman D. The ARTAS Hair Studio ® Technology is a Powerful Tool Integral to the Patient Consultation Experience.  Restoration robotics 2015:1-4.
  52. Gawad J, Bonde C. Artificial Intelligence : Future of Medicine and healthcare.   BioChemistry: An Indian Journal 2017;11:113.
  53. Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, Wang Y, Dong Q, Shen H, Wang Y. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol 2017;2:230-243.
  54. Lu S, Burton SL. Man vs Robots ? Future Challenges and Opportunities within Artificial Intelligence (AI) Health Care Education Model. Proceedings of the RAIS Conference 2017.