참고문헌 (63)

1. 1 Rajkomar A Dean J Kohane I Machine learning in medicine N Engl J Med 2019 380 14 1347 1358 30943338 

   상세보기

2. 2 Shimizu H Nakayama KI Artificial intelligence in oncology Cancer Sci 2020 111 5 1452 1460 32133724 

   상세보기

3. 3 Obermeyer Z Emanuel EJ Predicting the future - big data, machine learning, and clinical medicine N Engl J Med 2016 375 13 1216 1219 27682033 

   상세보기

4. 4 Jiang F Jiang Y Zhi H Dong Y Li H Ma S Artificial intelligence in healthcare: past, present and future Stroke Vasc Neurol 2017 2 4 230 243 29507784 

   상세보기

5. 5 Cruz JA Wishart DS Applications of machine learning in cancer prediction and prognosis Cancer Inform 2007 2 59 77 19458758 

6. 6 Ryu SM Seo SW Lee SH Novel prognostication of patients with spinal and pelvic chondrosarcoma using deep survival neural networks BMC Med Inform Decis Mak 2020 20 1 3 31907039 

7. 7 Pesapane F Codari M Sardanelli F Artificial intelligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine Eur Radiol Exp 2018 2 1 35 30353365 

8. 8 Ting DS Cheung CY Lim G Tan GS Quang ND Gan A Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes JAMA 2017 318 22 2211 2223 29234807 

   상세보기

9. 9 Han I Kim JH Park H Kim HS Seo SW Deep learning approach for survival prediction for patients with synovial sarcoma Tumour Biol 2018 40 9 1010428318799264 30261823 

   상세보기

10. 10 Lee J An JY Choi MG Park SH Kim ST Lee JH Deep learning-based survival analysis identified associations between molecular subtype and optimal adjuvant treatment of patients with gastric cancer JCO Clin Cancer Inform 2018 2 2 1 14 

11. 11 Kim JK Choi MJ Lee JS Hong JH Kim CS Seo SI A Deep Belief Network and Dempster-Shafer-Based Multiclassifier for the Pathology stage of prostate cancer J Healthc Eng 2018 2018 4651582 29755715 

12. 12 The Lancet Artificial intelligence in health care: within touching distance Lancet 2018 390 10114 2739 29303711 

13. 13 Kelly CJ Karthikesalingam A Suleyman M Corrado G King D Key challenges for delivering clinical impact with artificial intelligence BMC Med 2019 17 1 195 31665002 

    상세보기

14. 14 Erickson BJ Korfiatis P Akkus Z Kline TL Machine learning for medical imaging Radiographics 2017 37 2 505 515 28212054 

    상세보기

15. 15 Hu W Cai B Zhang A Calhoun VD Wang YP Deep collaborative learning with application to the study of multimodal brain development IEEE Trans Biomed Eng 2019 66 12 3346 3359 30872216 

    상세보기

16. 16 Patel V Armstrong D Ganguli M Roopra S Kantipudi N Albashir S Deep learning in gastrointestinal endoscopy Crit Rev Biomed Eng 2016 44 6 493 504 29431094 

    상세보기

17. 17 Komura D Ishikawa S Machine learning approaches for pathologic diagnosis Virchows Arch 2019 475 2 131 138 31222375 

18. 18 Currie G Hawk KE Rohren E Vial A Klein R Machine learning and deep learning in medical imaging: intelligent imaging J Med Imaging Radiat Sci 2019 50 4 477 487 31601480 

19. 19 Gulshan V Peng L Coram M Stumpe MC Wu D Narayanaswamy A Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs JAMA 2016 316 22 2402 2410 27898976 

    상세보기

20. 20 Ting DS Pasquale LR Peng L Campbell JP Lee AY Raman R Artificial intelligence and deep learning in ophthalmology Br J Ophthalmol 2019 103 2 167 175 30361278 

    상세보기

21. 21 Park HJ Kim SM La Yun B Jang M Kim B Jang JY A computer-aided diagnosis system using artificial intelligence for the diagnosis and characterization of breast masses on ultrasound: added value for the inexperienced breast radiologist Medicine (Baltimore) 2019 98 3 e14146 30653149 

22. 22 Kim K Kim S Lee YH Lee SH Lee HS Kim S Performance of the deep convolutional neural network based magnetic resonance image scoring algorithm for differentiating between tuberculous and pyogenic spondylitis Sci Rep 2018 8 1 13124 30177857 

23. 23 Topol EJ High-performance medicine: the convergence of human and artificial intelligence Nat Med 2019 25 1 44 56 30617339 

    상세보기

24. 24 Mori Y Kudo SE Misawa M Saito Y Ikematsu H Hotta K Real-time use of artificial intelligence in identification of diminutive polyps during colonoscopy: a prospective study Ann Intern Med 2018 169 6 357 366 30105375 

    상세보기

25. 25 Soffer S Ben-Cohen A Shimon O Amitai MM Greenspan H Klang E Convolutional neural networks for radiologic images: a radiologist's guide Radiology 2019 290 3 590 606 30694159 

    상세보기

26. 26 Fischer AM Varga-Szemes A Martin SS Sperl JI Sahbaee P Neumann D Artificial intelligence-based fully automated per lobe segmentation and emphysema-quantification based on chest computed tomography compared with global initiative for chronic obstructive lung disease severity of smokers J Thorac Imaging 2020 35 Suppl 1 S28 34 32235188 

27. 27 Philips IntelliSpace discovery Updated 2020 Accessed August 19, 2020 https://www.usa.philips.com/healthcare/product/HC881015/intellispace-discovery 

28. 28 WELCOMEAI Arterys - Cardio AI Updated 2020 Accessed August 19, 2020 https://www.welcome.ai/tech/healthcare/arterys-cardio-ai 

29. 29 Hannun AY Rajpurkar P Haghpanahi M Tison GH Bourn C Turakhia MP Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network Nat Med 2019 25 1 65 69 30617320 

    상세보기

30. 30 Vahlsing T Delbeck S Leonhardt S Heise HM Noninvasive monitoring of blood glucose using color-coded photoplethysmographic images of the illuminated fingertip within the visible and near-infrared range: opportunities and questions J Diabetes Sci Technol 2018 12 6 1169 1177 30222001 

31. 31 Fernandez-Carames TM Froiz-Miguez I Blanco-Novoa O Fraga-Lamas P Enabling the internet of mobile crowdsourcing health things: a mobile fog computing, blockchain and IoT based continuous glucose monitoring system for diabetes mellitus research and care Sensors (Basel) 2019 19 15 E3319 31357725 

32. 32 Mobihealthnews Medtronic, IBM Watson launch Sugar.IQ diabetes assistant Updated 2018 Accessed August 19, 2020 https://www.mobihealthnews.com/content/medtronic-ibm-watson-launch-sugariq-diabetes-assistant 

33. 33 Dankwa-Mullan I Rivo M Sepulveda M Park Y Snowdon J Rhee K Transforming diabetes care through artificial intelligence: the future is here Popul Health Manag 2019 22 3 229 242 30256722 

34. 34 PhysIQ PinpointIQ Updated 2020 Accessed August 19, 2020 https://www.physiq.com/solutions/pinpointiq/ 

35. 35 Philips Connected care solutions Updated 2020 Accessed August 19, 2020 http://www.thinkconnectedcare.philips.com/en.aspx 

36. 36 Ahmed MR Zhang Y Feng Z Lo B Inan OT Liao H Neuroimaging and machine learning for dementia diagnosis: recent advancements and future prospects IEEE Rev Biomed Eng 2019 12 19 33 30561351 

37. 37 Kim JP Kim J Park YH Park SB Lee JS Yoo S Machine learning based hierarchical classification of frontotemporal dementia and Alzheimer's disease Neuroimage Clin 2019 23 101811 30981204 

38. 38 Beccaria M Mellors TR Petion JS Rees CA Nasir M Systrom HK Preliminary investigation of human exhaled breath for tuberculosis diagnosis by multidimensional gas chromatography - time of flight mass spectrometry and machine learning J Chromatogr B Analyt Technol Biomed Life Sci 2018 1074-1075 46 50 

39. 39 Long NP Jung KH Yoon SJ Anh NH Nghi TD Kang YP Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers Oncotarget 2017 8 65 109436 109456 29312619 

    상세보기

40. 40 Healthcare IT News Next up for EHRs: vendors adding artificial intelligence into the workflow Updated 2018 Accessed August 20, 2020 https://www.healthcareitnews.com/news/next-ehrs-vendors-adding-artificial-intelligence-workflow 

41. 41 EvidNet Updated 2020 Accessed August 20, 2020 https://en.evidnet.com/ 

42. 42 Hripcsak G Duke JD Shah NH Reich CG Huser V Schuemie MJ Observational health data sciences and informatics (OHDSI): opportunities for observational researchers Stud Health Technol Inform 2015 216 574 578 26262116 

43. 43 IBM Clinical trial recruitment with AI Updated 2020 Accessed August 20, 2020 https://www.ibm.com/watson-health/learn/clinical-trial-recruitment 

44. 44 Azencott CA Machine learning and genomics: precision medicine versus patient privacy Philos Trans A Math Phys Eng Sci 2018 376 2128 20170350 30082298 

45. 45 Mooney SJ Pejaver V Big data in public health: terminology, machine learning, and privacy Annu Rev Public Health 2018 39 1 95 112 29261408 

    상세보기

46. 46 Kayaalp M Patient privacy in the era of big data Balkan Med J 2018 35 1 8 17 28903886 

    상세보기

47. 47 Sajid A Abbas H Data privacy in cloud-assisted healthcare systems: state of the art and future challenges J Med Syst 2016 40 6 155 27155893 

    상세보기

48. 48 You SC Lee S Cho SY Park H Jung S Cho J Conversion of National Health Insurance Service-national sample cohort (NHIS-NSC) database into observational medical outcomes partnership-common data model (OMOP-CDM) Stud Health Technol Inform 2017 245 467 470 29295138 

49. 49 Aldeen YA Salleh M Razzaque MA A comprehensive review on privacy preserving data mining Springerplus 2015 4 1 694 26587362 

    상세보기

50. 50 Lee J Sun J Wang F Wang S Jun CH Jiang X Privacy-preserving patient similarity learning in a federated environment: development and analysis JMIR Med Inform 2018 6 2 e20 29653917 

    상세보기

51. 51 Tariq RA Hackert PB Patient Confidentiality Treasure Island, FL StatPearls Publishing LLC. 2020 

52. 52 Pipersburgh J The push to increase the use of EHR technology by hospitals and physicians in the United States through the HITECH Act and the Medicare incentive program J Health Care Finance 2011 38 2 54 78 22372032 

    상세보기

53. 53 John B Are you ready for general data protection regulation? BMJ 2018 360 k941 29500167 

54. 54 Pelayo S Bras Da Costa S Leroy N Loiseau S Beuscart-Zephir MC Software as a medical device: regulatory critical issues Stud Health Technol Inform 2013 183 337 342 23388310 

    상세보기

55. 55 U.S. Food and Drug Administration Software as a Medical Device (SaMD) Updated 2018 Accessed August 20, 2020 https://www.fda.gov/medical-devices/digital-health/software-medical-device-samd 

56. 56 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 30617336 

    상세보기

57. 57 Nikkei Asian New rules to speed AI-based medicine in Japan Updated 2018 Accessed August 20, 2020 https://asia.nikkei.com/Economy/New-rules-to-speed-AI-based-medicine-in-Japan 

58. 58 The Korea Industry Daily Updated 2017 Accessed August 20, 2020 http://www.kidd.co.kr/news/198013 

59. 59 Executive Office of the President (US) Artificial intelligence, automation, and the economy Updated 2016 Accessed August 20, 2020 https://www.whitehouse.gov/sites/whitehouse.gov/files/images/EMBARGOED%20AI%20Economy%20Report.pdf 

60. 60 Executive Office of the President (US) The national artificial intelligence research and development strategic plan: 2019 update Updated 2019 Accessed August 20, 2020 https://www.nitrd.gov/pubs/National-AI-RD-Strategy-2019.pdf 

61. 61 Price WN 2nd Gerke S Cohen IG Potential liability for physicians using artificial intelligence JAMA 2019 322 18 1765 

    상세보기

62. 62 Reed C How should we regulate artificial intelligence? Philos Trans A Math Phys Eng Sci 2018 376 2128 20170360 30082306 

63. 63 Veeranki SP Kramer D Hayn D Jauk S Eggerth A Quehenberger F Is regular re-training of a predictive delirium model necessary after deployment in routine care? Stud Health Technol Inform 2019 260 186 191 31118336 

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