MACHINE LEARNING ALGORITHMS IMPLEMENTATION IN THE HEALTHCARE SYSTEM AS A PROSPECTIVE AREA FOR SCIENCE, HEALTHCARE, AND BUSINESS
Article PDF

Keywords

machine learning, biomedical data science, healthcare problems, biomedical data processing

Abstract views: 123
PDF Downloads: 31

How to Cite

Vasylevkyi , V., Stepanov , I., Koval , R., Soputnyak , M., Liutianska, N., Sheyko , V., & Stavnychyy , T. (2021). MACHINE LEARNING ALGORITHMS IMPLEMENTATION IN THE HEALTHCARE SYSTEM AS A PROSPECTIVE AREA FOR SCIENCE, HEALTHCARE, AND BUSINESS. Medical Science of Ukraine (MSU), 17(3), 98-109. https://doi.org/10.32345/2664-4738.3.2021.11

Abstract

Relevance. The current state of medicine is imperfect as in every other field. Some main discrete problems may be separated in diagnostics and disease management. Biomedical data operation difficulties are a serious limiting factor in solving crucial healthcare problems, represented in the statistically significant groups of diseases. Accumulation of life science data creates as possibilities as challenges to effectively utilize it in clinical practice. Machine learning-based tools are necessary for the generation of new insights and the discovery of new hidden patterns especially on big datasets. AI-based decisions may be successfully utilized for diagnosis of diseases, monitoring of general health, prediction of risks, treatment solutions, and biomedical knowledge generation.

Objective. To analyze the potential of machine learning algorithms in healthcare on exact existing problems and make a forecast of their development in near future.

Method. An analytical review of the literature on keywords from the scientometric databases Scopus, PubMed, Wiley. Search depth 7 years from 2013 to 2020.

Results. Analyzing the current general state of the healthcare system we separated the most relevant problems linked to diagnostics, treatment, and systemic management: diagnostics errors, delayed diagnostics (including during emergencies), overdiagnosis, bureaucracy, communication issues, and "handoff" difficulties. We examined details of the convenient decision-making process in the clinical environment in order to define exact points which may be significantly improved by AI-based decisions, among them: diagnosis of diseases, monitoring of general health, prediction of risks, treatment solutions, and biomedical knowledge generation. We defined machine learning algorithms as a prospective tool for disease diagnostics and management, as well as for new utilizable insights generation and big data processing.

Conclusion. Machine learning is a group of technologies that can become a cornerstone for dealing with various medical problems. But still, we have some problems to solve before the intense implementation of such tools in the healthcare system.

https://doi.org/10.32345/2664-4738.3.2021.11
Article PDF

References

Bhise V, Rajan SS, Sittig DF, Morgan RO, Chaudhary P, Singh H. Defining and Measuring Diagnostic Uncertainty in Medicine: A Systematic Review. J Gen In-tern Med. 2018 Jan;33(1):103-5. DOI: 10.1007/s11606-017-4164-1.

View at:

Scopus: https://link.springer.com/article/10.1007/s11606-017-4164-1

PubMed: https://pubmed.ncbi.nlm.nih.gov/28936618/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5756158/

Gunderson CG, Bilan VP, Holleck JL, Nickerson P, Cherry BM, Chui P, Bastian LA, Grimshaw AA, Rodwin BA. Prevalence of harmful diagnostic errors in hos-pitalised adults: a systematic review and meta-analysis. BMJ Qual Saf. 2020 Dec;29(12):1008-18. DOI: 10.1136/bmjqs-2019-010822.

View at:

Publisher Site: https://qualitysafety.bmj.com/content/29/12/1008

PubMed: https://pubmed.ncbi.nlm.nih.gov/32269070/

Singh H, Schiff GD, Graber ML, Onakpoya I, Thompson MJ. The global burden of diagnostic errors in primary care. BMJ Qual Saf. 2017 Jun;26(6):484-94. DOI: 10.1136/bmjqs-2016-005401.

View at:

Publisher Site: https://qualitysafety.bmj.com/content/26/6/484

PubMed: https://pubmed.ncbi.nlm.nih.gov/27530239/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5502242/

Carver N, Gupta V, Hipskind JE. Medical Error. 2020 Oct 5. In: StatPearls [In-ternet]. Treasure Island (FL): StatPearls Publishing; 2020 Jan. PMID: 28613514. Bookshelf ID: NBK430763

View at:

PubMed: https://pubmed.ncbi.nlm.nih.gov/28613514/

PubMed Central: https://www.ncbi.nlm.nih.gov/books/NBK430763/

Lippi G, Plebani M. Integrated diagnostics: the future of laboratory medicine? Bi-ochem Med (Zagreb). 2020 Feb 15;30(1):010501. DOI: 10.11613/BM.2020.010501.

View at:

Publisher Site: https://www.biochemia-medica.com/en/journal/30/1/10.11613/BM.2020.010501

PubMed: https://pubmed.ncbi.nlm.nih.gov/31839719/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904966/

World Health Organization. Assessing National Capacity for the Prevention and Control of Noncommunicable Diseases Global Survey. Global Survey 2015. Geneva, 2016

View at:

Publisher Site: https://apps.who.int/iris/handle/10665/246223

Fok PW, Lanzer P. Media sclerosis drives and localizes atherosclerosis in periph-eral arteries. PLoS One. 2018 Oct 26;13(10):e0205599. DOI: 10.1371/journal.pone.0205599

View at:

Publisher Site: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0205599

PubMed: https://pubmed.ncbi.nlm.nih.gov/30365531/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203409/

Taylor CJ, Ordóñez-Mena JM, Roalfe AK, Lay-Flurrie S, Jones NR, Marshall T, Hobbs FDR. Trends in survival after a diagnosis of heart failure in the United Kingdom 2000-2017: population based cohort study. BMJ. 2019 Feb 13;364:l223. DOI: 10.1136/bmj.l223.

View at:

Publisher Site: https://www.bmj.com/content/364/bmj.l223

PubMed: https://pubmed.ncbi.nlm.nih.gov/30760447/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372921/

Doust J, Glasziou P. Monitoring in clinical biochemistry. Clin Biochem Rev. 2013 Aug;34(2):85-92.

View at:

PubMed: https://pubmed.ncbi.nlm.nih.gov/24151344/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3799222/

Diagnostic Errors: Technical Series on Safer Primary Care. Geneva: World Health Organization; 2016. Licence: CC BY-NC-SA 3.0 IGO

View at:

Publisher Site: https://www.who.int/publications/i/item/diagnostic-errors

URL: https://apps.who.int/iris/bitstream/handle/10665/252410/9789241511636-eng.pdf

Newman-Toker DE, Moy E, Valente E, Coffey R, Hines AL. Missed diagnosis of stroke in the emergency department: a cross-sectional analysis of a large popu-lation-based sample. Diagnosis (Berl). 2014 Jun;1(2):155-66. DOI: 10.1515/dx-2013-0038.

View at:

Publisher Site: https://www.degruyter.com/document/doi/10.1515/dx-2013-0038/html

PubMed: https://pubmed.ncbi.nlm.nih.gov/28344918/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5361750/

Tarnutzer AA, Lee SH, Robinson KA, Wang Z, Edlow JA, Newman-Toker DE. ED misdiagnosis of cerebrovascular events in the era of modern neuroimag-ing: A meta-analysis. Neurology. 2017 Apr 11;88(15):1468-77. DOI: 10.1212/WNL.0000000000003814

View at:

Publisher Site: https://n.neurology.org/content/88/15/1468

PubMed: https://pubmed.ncbi.nlm.nih.gov/28356464/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5386439/

Zhang Y, Xia H, Wang Y, Chen L, Li S, Hussein IA, Wu Y, Shang Y, Yao S, Du R. The rate of missed diagnosis of lower-limb DVT by ultrasound amounts to 50% or so in patients without symptoms of DVT: A meta-analysis. Medicine (Baltimore). 2019 Sep;98(37):e17103. DOI: 10.1097/MD.0000000000017103.

View at:

Publisher Site: https://journals.lww.com/md-journal/Fulltext/2019/09130/The_rate_of_missed_diagnosis_of_lower_limb_DVT_by.32.aspx

PubMed: https://pubmed.ncbi.nlm.nih.gov/31517841/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6750306/

Walen S, Damoiseaux RA, Uil SM, van den Berg JW. Diagnostic delay of pulmonary embolism in primary and secondary care: a retrospective cohort study. Br J Gen Pract. 2016 Jun;66(647):e444-50. DOI: 10.3399/bjgp16X685201.

View at:

Publisher Site: https://bjgp.org/content/66/647/e444

PubMed: https://pubmed.ncbi.nlm.nih.gov/27114207/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4871310/

Michaels AD, Spinler SA, Leeper B, Ohman EM, Alexander KP, Newby LK, Ay H, Gibler WB; American Heart Association Acute Cardiac Care Committee of the Council on Clinical Cardiology, Council on Quality of Care and Outcomes Research; Council on Cardiopulmonary, Critical Care, Perioperative, and Resus-citation; Council on Cardiovascular Nursing; Stroke Council. Medication errors in acute cardiovascular and stroke patients: a scientific statement from the American Heart Association. Circulation. 2010 Apr 13;121(14):1664-82. DOI: 10.1161/CIR.0b013e3181d4b43e.

View at:

Publisher Site: https://www.ahajournals.org/doi/10.1161/CIR.0b013e3181d4b43e

PubMed: https://pubmed.ncbi.nlm.nih.gov/20308619/

Muroi M, Shen JJ, Angosta A. Association of medication errors with drug classifications, clinical units, and consequence of errors: Are they related? Appl Nurs Res. 2017 Feb;33:180-5. DOI: 10.1016/j.apnr.2016.12.002.

View at:

Scopus: https://www.sciencedirect.com/science/article/pii/S0897189716303767?via%3Dihub

PubMed: https://pubmed.ncbi.nlm.nih.gov/28096015/

Gelchu T, Abdela J. Drug therapy problems among patients with cardiovascu-lar disease admitted to the medical ward and had a follow-up at the ambulatory clinic of Hiwot Fana Specialized University Hospital: The case of a tertiary hospi-tal in eastern Ethiopia. SAGE Open Med. 2019 Jul 18;7:2050312119860401. DOI: 10.1177/2050312119860401.

View at:

Publisher Site: https://journals.sagepub.com/doi/10.1177/2050312119860401

PubMed: https://pubmed.ncbi.nlm.nih.gov/31367379/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6643177/

Reeve A, Simcox E, Turnbull D. Ageing and Parkinson's disease: why is ad-vancing age the biggest risk factor? Ageing Res Rev. 2014 Mar;14(100):19-30. DOI: 10.1016/j.arr.2014.01.004.

View at:

Scopus: https://www.sciencedirect.com/science/article/pii/S1568163714000051?via%3Dihub

PubMed: https://pubmed.ncbi.nlm.nih.gov/24503004/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3989046/

Rees RN, Acharya AP, Schrag A, Noyce AJ. An early diagnosis is not the same as a timely diagnosis of Parkinson's disease. F1000Res. 2018 Jul 18;7:F1000 Faculty Rev-1106. DOI: 10.12688/f1000research.14528.1.eCollection 2018

View at:

Publisher Site: https://f1000research.com/articles/7-1106/v1

PubMed: https://pubmed.ncbi.nlm.nih.gov/30079229/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053699/

Emamzadeh FN, Surguchov A. Parkinson's Disease: Biomarkers, Treatment, and Risk Factors. Front Neurosci. 2018 Aug 30;12:612. DOI: 10.3389/fnins.2018.00612.

View at:

Publisher Site: https://www.frontiersin.org/articles/10.3389/fnins.2018.00612/full

PubMed: https://pubmed.ncbi.nlm.nih.gov/30214392/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125353/

Obeso JA, Stamelou M, Goetz CG, Poewe W, Lang AE, Weintraub D, Burn D, Halliday GM, Bezard E, Przedborski S, Lehericy S, Brooks DJ, Rothwell JC, Hal-lett M, DeLong MR, Marras C, Tanner CM, Ross GW, Langston JW, Klein C, Bonifati V, Jankovic J, Lozano AM, Deuschl G, Bergman H, Tolosa E, Rodriguez-Violante M, Fahn S, Postuma RB, Berg D, Marek K, Standaert DG, Surmeier DJ, Olanow CW, Kordower JH, Calabresi P, Schapira AHV, Stoessl AJ. Past, present, and future of Parkinson's disease: A special essay on the 200th Anniversary of the Shaking Palsy. Mov Disord. 2017 Sep;32(9):1264-310. DOI: 10.1002/mds.27115.

View at:

Publisher Site: https://movementdisorders.onlinelibrary.wiley.com/doi/10.1002/mds.27115

PubMed: https://pubmed.ncbi.nlm.nih.gov/28887905/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5685546/

Adler CH, Beach TG, Hentz JG, Shill HA, Caviness JN, Driver-Dunckley E, Sabbagh MN, Sue LI, Jacobson SA, Belden CM, Dugger BN. Low clinical diag-nostic accuracy of early vs advanced Parkinson disease: clinicopathologic study. Neurology. 2014 Jul 29;83(5):406-12. DOI: 10.1212/WNL.0000000000000641.

View at:

Publisher Site: https://n.neurology.org/content/83/5/406

PubMed: https://pubmed.ncbi.nlm.nih.gov/24975862/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4132570/

Lane M, Yadav V. Multiple Sclerosis. Textbook of Natural Medicine. 2020:1587-1599.e3. DOI: 10.1016/B978-0-323-43044-9.00199-0.

View at:

Scopus: https://www.sciencedirect.com/science/article/pii/B9780323430449001990?via%3Dihub

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348625/

Culpepper WJ, Marrie RA, Langer-Gould A, Wallin MT, Campbell JD, Nelson LM, Kaye WE, Wagner L, Tremlett H, Chen LH, Leung S, Evans C, Yao S, LaRocca NG; United States Multiple Sclerosis Prevalence Workgroup (MSPWG). Validation of an algorithm for identifying MS cases in administrative health claims datasets. Neurology. 2019 Mar 5;92(10):e1016-e1028. DOI: 10.1212/WNL.0000000000007043.

View at:

Publisher Site: https://n.neurology.org/content/92/10/e1016

PubMed: https://pubmed.ncbi.nlm.nih.gov/30770432/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442008/

Mackenzie IS, Morant SV, Bloomfield GA, MacDonald TM, O'Riordan J. In-cidence and prevalence of multiple sclerosis in the UK 1990-2010: a descriptive study in the General Practice Research Database. Journal of Neurology, Neuro-surgery & Psychiatry. 2014;85:76-84. DOI: 10.1136/jnnp-2013-305450

View at:

Publisher Site: https://jnnp.bmj.com/content/85/1/76

PubMed: https://pubmed.ncbi.nlm.nih.gov/24052635/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888639/

Ziemssen T, Akgün K, Brück W. Molecular biomarkers in multiple sclerosis. J Neuroinflammation. 2019 Dec 23;16(1):272. DOI: 10.1186/s12974-019-1674-2.

View at:

Publisher Site: https://jneuroinflammation.biomedcentral.com/articles/10.1186/s12974-019-1674-2

Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, Cor-reale J, Fazekas F, Filippi M, Freedman MS, Fujihara K, Galetta SL, Hartung HP, Kappos L, Lublin FD, Marrie RA, Miller AE, Miller DH, Montalban X, Mowry EM, Sorensen PS, Tintoré M, Traboulsee AL, Trojano M, Uitdehaag BMJ, Vukusic S, Waubant E, Weinshenker BG, Reingold SC, Cohen JA. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018 Feb;17(2):162-73. DOI: 10.1016/S1474-4422(17)30470-2.

View at:

Publisher Site: https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(17)30470-2/fulltext

PubMed: https://pubmed.ncbi.nlm.nih.gov/29275977/

Kaisey M, Solomon AJ, Luu M, Giesser BS, Sicotte NL. Incidence of multiple sclerosis misdiagnosis in referrals to two academic centers. Mult Scler Relat Dis-ord. 2019 May;30:51-6. DOI: 10.1016/j.msard.2019.01.048.

View at:

Publisher Site: https://www.msard-journal.com/article/S2211-0348(19)30048-3/fulltext

PubMed: https://pubmed.ncbi.nlm.nih.gov/30738280/

Solomon AJ. Diagnosis, Differential Diagnosis, and Misdiagnosis of Multiple Sclerosis. Continuum (Minneap Minn). 2019 Jun;25(3):611-35. DOI: 10.1212/CON.0000000000000728.

View at:

Publisher Site: https://journals.lww.com/continuum/Abstract/2019/06000/Diagnosis,_Differential_Diagnosis,_and.5.aspx

PubMed: https://pubmed.ncbi.nlm.nih.gov/31162308/

2020 Alzheimer's disease facts and figures. Alzheimers Dement. 2020 Mar 10. DOI: 10.1002/alz.12068.

View at:

Publisher Site: https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.12068

PubMed: https://pubmed.ncbi.nlm.nih.gov/32157811/

World Health Organization. Global action plan on the public health response to dementia 2017-2025. Geneva 2017. Licence: CC BY-NC-SA 3.0 IGO.

View at:

Publisher Site: https://apps.who.int/iris/handle/10665/259615

URL: https://apps.who.int/iris/bitstream/handle/10665/259615/9789241513487-eng.pdf?sequence=1

Bloudek LM, Spackman DE, Blankenburg M, Sullivan SD. Review and meta-analysis of biomarkers and diagnostic imaging in Alzheimer's disease. J Alz-heimers Dis. 2011;26(4):627-45. DOI: 10.3233/JAD-2011-110458.

View at:

Publisher Site: https://content.iospress.com/articles/journal-of-alzheimers-disease/jad110458

PubMed: https://pubmed.ncbi.nlm.nih.gov/21694448/

McKhann GM, Albert MS, Sperling RA. Changing diagnostic concepts of Alz-heimer’s disease. In: Hampel H, Carrillo MC, eds. Alzheimer’s disease – Modern-izing concept, biological diagnosis and therapy. Basel, Switzerland: Karger; 2012: p. 115‐21.

View at:

Publisher Site: https://www.karger.com/Book/Home/256724

Scielo: https://scielo.isciii.es/scielo.php?script=sci_arttext&pid=S0213-61632013000200007

Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020 Jan;70(1):7-30. DOI: 10.3322/caac.21590.

View at:

Publisher Site: https://acsjournals.onlinelibrary.wiley.com/doi/10.3322/caac.21590

Morris LG, Tuttle RM, Davies L. Changing Trends in the Incidence of Thyroid Cancer in the United States. JAMA Otolaryngol Head Neck Surg. 2016 Jul 1;142(7):709-11. DOI: 10.1001/jamaoto.2016.0230.

View at:

Publisher Site: https://jamanetwork.com/journals/jamaotolaryngology/fullarticle/2513194

PubMed: https://pubmed.ncbi.nlm.nih.gov/27078686/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4956490/

Ahn HS, Kim HJ, Welch HG. Korea’s thyroid-cancer "Epidemic" – screening and overdiagnosis. N Engl J Med. 2014 Nov 6;371(19):1765-7. DOI: 10.1056/NEJMp1409841.

View at:

Publisher Site: https://www.nejm.org/doi/10.1056/NEJMp1409841

PubMed: https://pubmed.ncbi.nlm.nih.gov/25372084/

Ahn HS, Welch HG. South Korea’s Thyroid-Cancer "Epidemic" – Turning the Tide. N Engl J Med. 2015 Dec 10;373(24):2389-90. DOI: 10.1056/NEJMc1507622.

View at:

Publisher Site: https://www.nejm.org/doi/10.1056/NEJMc1507622

PubMed: https://pubmed.ncbi.nlm.nih.gov/26650173/

Theoharis CG, Schofield KM, Hammers L, Udelsman R, Chhieng DC. The Be-thesda thyroid fine-needle aspiration classification system: year 1 at an academic institution. Thyroid. 2009 Nov;19(11):1215-23. DOI: 10.1089/thy.2009.0155.

View at:

Publisher Site: https://www.liebertpub.com/doi/10.1089/thy.2009.0155

PubMed: https://pubmed.ncbi.nlm.nih.gov/19888859/

Wang W, Chang J, Jia B, Liu J. The Blood Biomarkers of Thyroid Cancer. Cancer Manag Res. 2020 Jul 6;12:5431-8. DOI: 10.2147/CMAR.S261170.

View at:

Publisher Site: https://www.dovepress.com/the-blood-biomarkers-of-thyroid-cancer-peer-reviewed-fulltext-article-CMAR

Ilic D, Neuberger MM, Djulbegovic M, Dahm P. Screening for prostate cancer. Cochrane Database Syst Rev. 2013 Jan 31;(1):CD004720. DOI: 10.1002/14651858.CD004720.pub3.

View at:

Publisher Site: https://www.cochranelibrary.com/cdsr/doi/10.1002/14651858.CD004720.pub3/abstract

PubMed: https://pubmed.ncbi.nlm.nih.gov/23440794/

Prabhu V, Lee T, McClintock TR, Lepor H. Short-, Intermediate-, and Long-term Quality of Life Outcomes Following Radical Prostatectomy for Clinically Localized Prostate Cancer. Rev Urol. 2013;15(4):161-77.

View at:

PubMed: https://pubmed.ncbi.nlm.nih.gov/24659913/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922321/

Qu M, Ren SC, Sun YH. Current early diagnostic biomarkers of prostate can-cer. Asian J Androl. 2014 Jul-Aug;16(4):549-54. DOI: 10.4103/1008-682X.129211.

View at:

Publisher Site: https://www.ajandrology.com/article.asp?issn=1008-682X;year=2014;volume=16;issue=4;spage=549;epage=554;aulast=Qu

PubMed: https://pubmed.ncbi.nlm.nih.gov/24830695/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4104079/

Stenvinkel P. Chronic kidney disease: a public health priority and harbinger of premature cardiovascular disease. J Intern Med. 2010 Nov;268(5):456-67. DOI: 10.1111/j.1365-2796.2010.02269.x.

View at:

Publisher Site: https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2796.2010.02269.x

PubMed: https://pubmed.ncbi.nlm.nih.gov/20809922/

Uchino S, Kellum JA, Bellomo R, Doig GS, Morimatsu H, Morgera S, Schetz M, Tan I, Bouman C, Macedo E, Gibney N, Tolwani A, Ronco C; Beginning and Ending Supportive Therapy for the Kidney (BEST Kidney) Investigators. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA. 2005 Aug 17;294(7):813-8. DOI: 10.1001/jama.294.7.813.

View at:

Publisher Site: https://jamanetwork.com/journals/jama/fullarticle/201386

PubMed: https://pubmed.ncbi.nlm.nih.gov/16106006/

Bosch JP. Renal reserve: a functional view of glomerular filtration rate. Semin Nephrol. 1995 Sep;15(5):381-5.

View at:

PubMed: https://pubmed.ncbi.nlm.nih.gov/8525139/

Herrera J, Rodríguez-Iturbe B. Stimulation of tubular secretion of creatinine in health and in conditions associated with reduced nephron mass. Evidence for a tubular functional reserve. Nephrol Dial Transplant. 1998 Mar;13(3):623-9. DOI: 10.1093/ndt/13.3.623.

View at:

Academic: https://academic.oup.com/ndt/article/13/3/623/1848120

Glassock RJ, Denic A, Rule AD. The conundrums of chronic kidney disease and aging. J Nephrol. 2017 Aug;30(4):477-83. DOI: 10.1007/s40620-016-0362-x.

View at:

Scopus: https://link.springer.com/article/10.1007%2Fs40620-016-0362-x

PubMed: https://pubmed.ncbi.nlm.nih.gov/27885585/

Jiang J, Li X, Zhao C, Guan Y, Yu Q. Learning and inference in knowledge-based probabilistic model for medical diagnosis. Knowledge-Based Systems. 2017;138: 58-68, ISSN 0950-7051. DOI: 10.1016/J.KNOSYS.2017.09.030.

View at:

Scopus: https://www.sciencedirect.com/science/article/abs/pii/S0950705117304495?via%3Dihub

Publisher Site: https://dl.acm.org/doi/abs/10.1016/j.knosys.2017.09.030

Booksc: https://ur.booksc.eu/book/67269701/cc2c8c

Seh AH, Zarour M, Alenezi M, Sarkar AK, Agrawal A, Kumar R, Khan RA. Healthcare Data Breaches: Insights and Implications. Healthcare (Basel). 2020 May 13;8(2):133. DOI: 10.3390/healthcare8020133.

View at:

Publisher Site: https://www.mdpi.com/2227-9032/8/2/133

PubMed: https://pubmed.ncbi.nlm.nih.gov/32414183/

PubMed Central: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349636/

Cortes C, Vapnik V. Support-vector networks. Mach Learn. 1995; 20: 273-97. DOI: 10.1007/BF00994018

View at:

Scopus: https://link.springer.com/article/10.1007/BF00994018

URL: https://link.springer.com/content/pdf/10.1007/bf00994018.pdf

McCallum A, Nigam K. A comparison of event models for naive bayes text classification. In: AAAI-98 workshop on learning for text categorization. 1998, July;752(1): 41-8.

View at:

Bibsonomy: https://www.bibsonomy.org/bibtex/2fa46d1cc0dd56ab40a7f722e569a1fd3/jil

URL: https://www.cs.cmu.edu/~knigam/papers/multinomial-aaaiws98.pdf

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.