Primena veštačke inteligencije u upravljanju zdravstvenim sistemom u Republici Srbiji: Povećanje efikasnosti, prediktivnog kapaciteta i donošenja odluka
Ključne reči:
veštačka inteligencija, menadžment u zdravstvu, prediktivna analitika, sistemi za podršku odlučivanju, optimizacija resursa, Srbija
Sažetak
Veštačka inteligencija (AI) nudi transformativni potencijal u upravljanju zdravstvenom zaštitom poboljšavajući prediktivnu analitiku, optimizujući alokaciju resursa i podržavajući kliničko donošenje odluka. Ova studija ispituje primene veštačke inteligencije u srpskim zdravstvenim ustanovama, fokusirajući se na operativnu efikasnost i poboljšane ishode pacijenata. Koristeći statističke metode kao što su ANOVA i regresija, nalazi pokazuju značajne koristi od usvajanja AI, dok infrastrukturna i etička razmatranja ostaju kritična za uspešnu integraciju. Studija pruža osnovu za kreatore politike koji imaju za cilj da ugrade veštačku inteligenciju u zdravstveni sistem Srbije, baveći se i potencijalnim poboljšanjima i izazovima.
Reference
1. Wang Y, Kung LA, Byrd TA. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technol Forecast Soc Change. 2018;126:3-13.
2. Esteva A, Robicquet A, Ramsundar B, et al. A guide to deep learning in healthcare. Nat Med. 2019;25(1):24-29.
3. Topol EJ. High-performance medicine: The convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56.
4. Beam AL, Kohane IS. Big data and machine learning in health care. JAMA. 2018;319(13):1317-1318.
5. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-98.
6. Krittanawong C, Zhang H, Wang Z, Aydar M, Kitai T. Artificial intelligence in precision cardiovascular medicine. J Am Coll Cardiol. 2017;69(21):2657-2664.
7. Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018;2(10):719-731.
8. Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243.
9. Rajpurkar P, Irvin J, Ball RL, et al. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Med. 2018;15(11).
10. Esteva A, Chou K, Yeung S, Naik N, Madani A, Mottaghi A. AI for radiology. Med Phys. 2021;48(6):16-22.
11. Chen JH, Asch SM. Machine learning and prediction in medicine - beyond the peak of inflated expectations. N Engl J Med. 2017;376(26):2507-2509.
12. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K. The practical implementation of artificial intelligence technologies in medicine. Nat Med. 2019;25(1):30-36.
13. London AJ. Artificial intelligence and black-box medical decisions: Accuracy versus explainability. Hastings Cent Rep. 2019;49(1):15-21.
14. Shortliffe EH, Sepúlveda MJ. Clinical decision support in the era of artificial intelligence. JAMA. 2018;320(21):2199-2200.
15. Matheny ME, Whicher D, Thadaney Israni S. Artificial intelligence in health care: A report from the national academy of medicine. JAMA. 2020;323(6):509-510.
16. McKinney SM, Sieniek M, Godbole V, et al. International evaluation of an AI system for breast cancer screening. Nature. 2020;577(7788):89-94.
17. Price WN. Big data and black-box medical algorithms. Sci Transl Med. 2018;10(471).
18. Obermeyer Z, Emanuel EJ. Predicting the future - big data, machine learning, and clinical medicine. N Engl J Med. 2016;375(13):1216-1219.
19. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366(6464):447-453.
20. Char DS, Shah NH, Magnus D. Implementing machine learning in health care - addressing ethical challenges. N Engl J Med. 2018;378(11):981-983.
21. Deo RC. Machine learning in medicine. Circulation. 2015;132(20):1920-1930.
22. Reddy S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare delivery. J R Soc Med. 2019;112(1):22-28.
23. Topol EJ. Deep medicine: How artificial intelligence can make healthcare human again. Basic Books. 2019.
24. Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism. 2017;69S.
25. Johnson KW, Torres Soto J, Glicksberg BS, et al. Artificial intelligence in cardiology. J Am Coll Cardiol. 2018;71(23):2668-2679.
26. Murdoch TB, Detsky AS. The inevitable application of big data to health care. JAMA. 2013;309(13):1351-1352.
27. Amann J, Blasimme A, Vayena E, Frey D, Madai VI. Explainability for artificial intelligence in healthcare: A multidisciplinary perspective. BMC Med Inform Decis Mak. 2020;20(1):310.
28. Parmar C, Barry JD, Hosny A, Aerts HJ. Machine learning with radiomic features. Radiographics. 2018;38(6):1872-1882.
29. McGough SF, Thigpen S, Samore MH, Weir CR, Drews FA. The use of artificial intelligence in clinical decision support. BMC Med Inform Decis Mak. 2018;18(1):65.
30. Mesko B, Hetenyi G, Gyoz E. Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res. 2018;18(1):545.
31. Miller DD, Brown EW. Artificial intelligence in medical practice: The question to the answer? Am J Med. 2018;131(2):129-133.
32. Dilsizian SE, Siegel EL. Artificial intelligence in medicine and cardiac imaging: Harnessing big data and advanced computing to provide personalized medical diagnosis and treatment. Curr Cardiol Rep. 2014;16(1):441.
33. Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: Benefits, risks, and strategies for success. NPJ Digit Med. 2020;3:17.
34. Davenport TH, Hongsermeier T, McCord KA. Using artificial intelligence to improve hospital inpatient care. NEJM Catal Innov Care Deliv. 2021;2(1):6-14.
35. Chen M, Decary M. Artificial intelligence in healthcare: An essential guide for the public and policy makers. BMC Med Inform Decis Mak. 2020;20(1):1-16.
36. Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115-118.
37. Tang F, Ishwaran H, VanderWeele TJ. Artificial intelligence in healthcare: A critical analysis. JAMA Netw Open. 2020;3(5).
38. Kulkarni S, Seneviratne N, Baig MS, Khan AHA. Artificial intelligence in medicine: Where are we now? Acad Radiol. 2020;27(1):62-70.
39. Cabitza F, Rasoini R, Gensini GF. Unintended consequences of machine learning in medicine. JAMA. 2017;318(6):517-518.
40. Lee J, Doyle-Lindrud S. The influence of artificial intelligence on oncology nursing. Clin J Oncol Nurs. 2020;24(4):331-334.
41. Bini SA. Artificial intelligence, machine learning, deep learning, and cognitive computing: What do these terms mean and how will they impact health care? J Arthroplasty. 2018;33(8):2358-2361.
42. Reardon S. Machine learning gets to the root of machine-learning biases. Nature. 2020;586(7827):483-484.
2. Esteva A, Robicquet A, Ramsundar B, et al. A guide to deep learning in healthcare. Nat Med. 2019;25(1):24-29.
3. Topol EJ. High-performance medicine: The convergence of human and artificial intelligence. Nat Med. 2019;25(1):44-56.
4. Beam AL, Kohane IS. Big data and machine learning in health care. JAMA. 2018;319(13):1317-1318.
5. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-98.
6. Krittanawong C, Zhang H, Wang Z, Aydar M, Kitai T. Artificial intelligence in precision cardiovascular medicine. J Am Coll Cardiol. 2017;69(21):2657-2664.
7. Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018;2(10):719-731.
8. Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243.
9. Rajpurkar P, Irvin J, Ball RL, et al. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Med. 2018;15(11).
10. Esteva A, Chou K, Yeung S, Naik N, Madani A, Mottaghi A. AI for radiology. Med Phys. 2021;48(6):16-22.
11. Chen JH, Asch SM. Machine learning and prediction in medicine - beyond the peak of inflated expectations. N Engl J Med. 2017;376(26):2507-2509.
12. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K. The practical implementation of artificial intelligence technologies in medicine. Nat Med. 2019;25(1):30-36.
13. London AJ. Artificial intelligence and black-box medical decisions: Accuracy versus explainability. Hastings Cent Rep. 2019;49(1):15-21.
14. Shortliffe EH, Sepúlveda MJ. Clinical decision support in the era of artificial intelligence. JAMA. 2018;320(21):2199-2200.
15. Matheny ME, Whicher D, Thadaney Israni S. Artificial intelligence in health care: A report from the national academy of medicine. JAMA. 2020;323(6):509-510.
16. McKinney SM, Sieniek M, Godbole V, et al. International evaluation of an AI system for breast cancer screening. Nature. 2020;577(7788):89-94.
17. Price WN. Big data and black-box medical algorithms. Sci Transl Med. 2018;10(471).
18. Obermeyer Z, Emanuel EJ. Predicting the future - big data, machine learning, and clinical medicine. N Engl J Med. 2016;375(13):1216-1219.
19. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019;366(6464):447-453.
20. Char DS, Shah NH, Magnus D. Implementing machine learning in health care - addressing ethical challenges. N Engl J Med. 2018;378(11):981-983.
21. Deo RC. Machine learning in medicine. Circulation. 2015;132(20):1920-1930.
22. Reddy S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare delivery. J R Soc Med. 2019;112(1):22-28.
23. Topol EJ. Deep medicine: How artificial intelligence can make healthcare human again. Basic Books. 2019.
24. Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism. 2017;69S.
25. Johnson KW, Torres Soto J, Glicksberg BS, et al. Artificial intelligence in cardiology. J Am Coll Cardiol. 2018;71(23):2668-2679.
26. Murdoch TB, Detsky AS. The inevitable application of big data to health care. JAMA. 2013;309(13):1351-1352.
27. Amann J, Blasimme A, Vayena E, Frey D, Madai VI. Explainability for artificial intelligence in healthcare: A multidisciplinary perspective. BMC Med Inform Decis Mak. 2020;20(1):310.
28. Parmar C, Barry JD, Hosny A, Aerts HJ. Machine learning with radiomic features. Radiographics. 2018;38(6):1872-1882.
29. McGough SF, Thigpen S, Samore MH, Weir CR, Drews FA. The use of artificial intelligence in clinical decision support. BMC Med Inform Decis Mak. 2018;18(1):65.
30. Mesko B, Hetenyi G, Gyoz E. Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Serv Res. 2018;18(1):545.
31. Miller DD, Brown EW. Artificial intelligence in medical practice: The question to the answer? Am J Med. 2018;131(2):129-133.
32. Dilsizian SE, Siegel EL. Artificial intelligence in medicine and cardiac imaging: Harnessing big data and advanced computing to provide personalized medical diagnosis and treatment. Curr Cardiol Rep. 2014;16(1):441.
33. Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: Benefits, risks, and strategies for success. NPJ Digit Med. 2020;3:17.
34. Davenport TH, Hongsermeier T, McCord KA. Using artificial intelligence to improve hospital inpatient care. NEJM Catal Innov Care Deliv. 2021;2(1):6-14.
35. Chen M, Decary M. Artificial intelligence in healthcare: An essential guide for the public and policy makers. BMC Med Inform Decis Mak. 2020;20(1):1-16.
36. Esteva A, Kuprel B, Novoa RA, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115-118.
37. Tang F, Ishwaran H, VanderWeele TJ. Artificial intelligence in healthcare: A critical analysis. JAMA Netw Open. 2020;3(5).
38. Kulkarni S, Seneviratne N, Baig MS, Khan AHA. Artificial intelligence in medicine: Where are we now? Acad Radiol. 2020;27(1):62-70.
39. Cabitza F, Rasoini R, Gensini GF. Unintended consequences of machine learning in medicine. JAMA. 2017;318(6):517-518.
40. Lee J, Doyle-Lindrud S. The influence of artificial intelligence on oncology nursing. Clin J Oncol Nurs. 2020;24(4):331-334.
41. Bini SA. Artificial intelligence, machine learning, deep learning, and cognitive computing: What do these terms mean and how will they impact health care? J Arthroplasty. 2018;33(8):2358-2361.
42. Reardon S. Machine learning gets to the root of machine-learning biases. Nature. 2020;586(7827):483-484.
Objavljeno
2025/11/19
Broj časopisa
Rubrika
Originalni rad / Original article