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Yıl 2023, Cilt: 1 Sayı: 1, 54 - 74, 02.02.2024

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Kaynakça

  • [1] Emilia Apostolova, Amit Uppal, Jessica E Galarraga, Ioannis Koutroulis, Tim Tschampel, Tony Wang, and Tom Velez. Towards reliable ards clinical decision support: Ards patient analytics with free-text and structured emr data. In AMIA Annual Symposium Proceedings, volume 2019, page 228. American Medical Informatics Association, 2019.
  • [2] Richard F Averill and Rhonda R Butler. Misperceptions, misinformation, and misrepresentations: The icd-10-cm/pcssaga. Journal of AHIMA, 2013.
  • [3] Lauren B Ball, Steven C Macdonald, Joshua A Mott, and Ruth A Etzel. Carbon monoxide-related injury estimation using icd-coded data: methodologic implications for public health surveillance. Archives of Environmental & Occupational Health, 60(3):119–127, 2005.
  • [4] Tal Baumel, Jumana Nassour-Kassis, Raphael Cohen, Michael Elhadad, and Noemie Elhadad. Multi-label classification of patient notes a case study on icd code assignment. arXiv preprint arXiv:1709.09587, 2017.
  • [5] Curtis Benesch, DM Witter, AL Wilder, PW Duncan, GP Samsa, and DB Matchar. Inaccuracy of the international classification of diseases (icd-9-cm) in identifying the diagnosis of ischemic cerebrovascular disease. Neurology, 49(3):660–664, 1997.
  • [6] William R Best, Shukri F Khuri, Maureen Phelan, Kwan Hur, William G Henderson, John G Demakis, and Jennifer Daley. Identifying patient preoperative risk factors and postoperative adverse events in administrative databases: results from the department of veterans affairs national surgical quality improvement program. Journal of the American College of Surgeons, 194(3):257–266, 2002.
  • [7] Ankeet S Bhatt, Erin E McElrath, Brian L Claggett, Deepak L Bhatt, Dale S Adler, Scott D Solomon, and Muthiah Vaduganathan. Accuracy of icd-10 diagnostic codes to identify covid-19 among hospitalized patients. Journal of general internal medicine, 36(8):2532–2535, 2021.
  • [8] Panagiota Birmpili, Eleanor Atkins, Qiuju Li, Amundeep S Johal, Sam Waton, Robin Williams, Arun D Pherwani, and David A Cromwell. Evaluation of the icd-10 system in coding revascularisation procedures in patients with peripheral arterial disease in england: A retrospective cohort study using national administrative and clinical databases. EClinicalMedicine, 55, 2023.
  • [9] Donna Z Bliss, Laurie McNichol, Donna Cartwright, and Mikel Gray. Practice alert: new icd-10 codes for masd. Journal of Wound, Ostomy, and Continence Nursing, 49(1):15, 2022.
  • [10] Jacob Bodilsen, Steffen Leth, Stig Lønberg Nielsen, Jon Gitz Holler, Thomas Benfield, and Lars Haukali Omland. Positive predictive value of icd-10 diagnosis codes for covid-19. Clinical Epidemiology, pages 367–372, 2021.
  • [11] Taxiarchis Botsis, Gunnar Hartvigsen, Fei Chen, and Chunhua Weng. Secondary use of ehr: data quality issues and informatics opportunities. Summit on translational bioinformatics, 2010:1, 2010.
  • [12] Nele Brusselaers, Stan Monstrey, Dirk Vogelaers, Eric Hoste, and Stijn Blot. Severe burn injury in europe: a systematic review of the incidence, etiology, morbidity, and mortality. Critical care, 14(5):1–12, 2010.
  • [13] Li Cao and John E Morley. Sarcopenia is recognized as an independent condition by an international classification of disease, tenth revision, clinical modification (icd-10-cm) code. Journal of the American Medical Directors Association, 17 (8): 675–677, 2016.
  • [14] Donna J Cartwright. Icd-9-cm to icd-10-cm codes: what? why? how?, 2013.
  • [15] Finneas Catling, Georgios P Spithourakis, and Sebastian Riedel. Towards automated clinical coding. International journal of medical informatics, 120:50–61, 2018.
  • [16] Pei-Fu Chen, Ssu-Ming Wang, Wei-Chih Liao, Lu-Cheng Kuo, Kuan-Chih Chen, Yu-Cheng Lin, Chi-Yu Yang, Chi-Hao Chiu, Shu-Chih Chang, Feipei Lai, et al. Automatic icd-10 coding and training system: deep neural network based on supervised learning. JMIR Medical Informatics, 9(8):e23230, 2021.
  • [17] Abdelahad Chraibi, David Delerue, Julien Taillard, Ismat Chaib Draa, Regis Beuscart, Arnaud Hansske, et al. A deep learning framework for automated icd-10 coding. In MIE, pages 347–351, 2021.
  • [18] Jillian M Clark and Ruth Marshall. Utilising international statistical classification of diseases and related health conditions (icd)-10 australian modification classifications of “health conditions” to achieve population health surveillance in an australian spinal cord injury cohort. Spinal Cord, 60(8):746–756, 2022.
  • [19] William O Cleverley and James O Cleverley. Essentials of health care finance. Jones & Bartlett Learning, 2017.
  • [20] Linda B Cottler and Bridget F Grant. Characteristics of nosologically informative data sets that address key diagnostic issues facing the diagnostic and statistical manual of mental disorders, (dsm-v) and international classification of diseases, (icd-11) substance use disorders workgroups. Addiction, 101:161–169, 2006.
  • [21] Andrei Michael Dreyer. Using Transformers to assign ICD codes to medical notes. PhD thesis, University of Stellenbosch, 2023.
  • [22] Lærke Storgaard Duerlund, Shakil Shakar, Henrik Nielsen, and Jacob Bodilsen. Positive predictive value of the icd-10 diagnosis code for long-covid. Clinical epidemiology, pages 141–148, 2022.
  • [23] John Dumay and James Guthrie. Involuntary disclosure of intellectual capital: is it relevant? Journal of Intellectual Capital, 18(1):29–44, 2017.
  • [24] Swetha Duraiswamy, Amanda Ignacio, Janice Weinberg, Sabrina E Sanchez, David R Flum, Michael K Paasche-Orlow, Kelly M Kenzik, Jennifer F Tseng, and Frederick Thurston Drake. Comparative accuracy of icd-9 vs icd-10 codes for acute appendicitis. Journal of the American College of Surgeons, 234(3):377–383, 2022.
  • [25] Cathy A Eastwood, Danielle A Southern, Chelsea Doktorchik, Shahreen Khair, Denise Cullen, Alicia Boxill, Malgorzata Maciszewski, Lucia Otero Varela, William Ghali, Lori Moskal, et al. Training and experience of coding with the world health organization’s international classification of diseases, eleventh revision. Health Information Management Journal, 52 (2): 92–100, 2023.
  • [26] Thomas J Falen and Aaron Liberman. Learning to code with icd-9-cm for health information management and health services administration 2006. Lippincott Williams & Wilkins, 2005.
  • [27] Samah Jamal Fodeh, Brenda T Fenton, Rixin Wang, Melissa Skanderson, Hamada Altalib, Deena Kuruvilla, Emmanuelle Schindler, Sally Haskell, Cynthia Brandt, and Jason J Sico. Understanding headache classification coding within the veterans health administration using icd-9-cm and icd-10-cm in fiscal years 2014–2017. Plos one, 18(1):e0279163, 2023.
  • [28] Kin Wah Fung, Rachel Richesson, Michelle Smerek, Katherine C Pereira, Beverly B Green, Ashwin Patkar, Megan Clowse, Alan Bauck, and Olivier Bodenreider. Preparing for the icd-10-cm transition: automated methods for translating icd codes in clinical phenotype definitions. eGEMs, 4(1), 2016.
  • [29] Kin Wah Fung, Julia Xu, and Olivier Bodenreider. The new international classification of diseases 11th edition: a comparative analysis with icd-10 and icd-10-cm. Journal of the American Medical Informatics Association, 27 (5) : 738–746, 2020.
  • [30] Jennifer H Garvin and C C S RHIA. Evaluation of public health reporting using ICD-10-CM. In APHA Scientific Session and Event Listing, 2006.
  • [31] Mikel Gray, Donna Z Bliss, and Laurie McNichol. Moisture-associated skin damage: expanding and updating practice based on the newest icd-10-cm codes. Journal of Wound, Ostomy and Continence Nursing, 49(2):143–151, 2022.
  • [32] Adi V Gundlapalli, Amy M Lavery, Tegan K Boehmer, Michael J Beach, Henry T Walke, Paul D Sutton, and Robert N Anderson. Death certificate–based icd-10 diagnosis codes for covid-19 mortality surveillance—united states, january–december 2020. Morbidity and Mortality Weekly Report, 70(14):523, 2021.
  • [33] Yi Guo, Zhaoyi Chen, Ke Xu, Thomas J George, Yonghui Wu, William Hogan, Elizabeth A Shenkman, and Jiang Bian. International classification of diseases, tenth revision, clinical modification social determinants of health codes are poorly used in electronic health records. Medicine, 99(52), 2020.
  • [34] James E Harrison, Stefanie Weber, Robert Jakob, and Christopher G Chute. Icd-11: an international classification of diseases for the twenty-first century. BMC medical informatics and decision making, 21(6):1–10, 2021.
  • [35] Elias Hossain, Rajib Rana, Niall Higgins, Jeffrey Soar, Prabal Datta Barua, Anthony R Pisani, et al. Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review. arXiv preprint arXiv:2306.12834, 2023.
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  • [37] Rajvir Kaur and Jeewani Anupama Ginige. Comparative analysis of algorithmic approaches for auto-coding with icd10-am and achi. Studies in health technology and informatics, 252:73–79, 2018.
  • [38] Rajvir Kaur, Jeewani Anupama Ginige, and Oliver Obst. A systematic literature review of automated icd coding and classification systems using discharge summaries. arXiv preprint arXiv:2107.10652, 2021.
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  • [41] Garrett Keim, Amanda O’Halloran, Martha Kienzle, Alexis Topjian, Robert Berg, Robert Sutton, Nadir Yehya, and Ryan Morgan. 259: Icd-10 switch decreased in-hospital cardiac arrest incidence: Concern for exposure misclassification. Critical Care Medicine, 51(1):114, 2023.
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  • [44] Kristine E Lynch, Benjamin Viernes, Elise Gatsby, Scott L DuVall, Barbara E Jones, Tamara L Box, Craig Kreisler, and ´ Makoto Jones. Positive predictive value of covid-19 icd-10 diagnosis codes across calendar time and clinical setting. Clinical Epidemiology, pages 1011–1018, 2021.
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SURVEY OF THE DEVELOPMENT PROCESSES AND EVOLUTION OF THE INTERNATIONAL CLASSIFICATION OF DISEASES

Yıl 2023, Cilt: 1 Sayı: 1, 54 - 74, 02.02.2024

Öz

The International Classification of Diseases (ICDs) has a global application in epidemiological research, health administration, and diagnostic studies. The ICD is a classification system within the healthcare system, developed and endorsed by the World Health Organization (WHO) to provide a comprehensive range of diagnostic codes for categorizing diseases. It encompasses exhaustive classifications of diverse indications, manifestations, abnormal findings, grievances, societal circumstances, and extrinsic factors contributing to injury or illness. This system relied entirely on clinical data sets that are collected by officials, on the basis of which the International Classification of Diseases is coded for many purposes such as billing systems, determining the type of disease, and the types of treatments used. Recently, what is known as the electronic health record system appeared to be adopted in writing clinical notes, which led researchers to integrate modern technology in Natural Language Processing in addition to Machine Learning and deep learning techniques to code the International Classification of Diseases in a more effective and accurate way. The factors mentioned helped shed more light on the importance of this system, its objectives, and the developments that have been made on it since its inception. and also led us in this paper to conduct a comprehensive survey on the latest technologies prepared by researchers in the field of classification and coding of diseases and what are the processes that have been adopted in this regard.

Kaynakça

  • [1] Emilia Apostolova, Amit Uppal, Jessica E Galarraga, Ioannis Koutroulis, Tim Tschampel, Tony Wang, and Tom Velez. Towards reliable ards clinical decision support: Ards patient analytics with free-text and structured emr data. In AMIA Annual Symposium Proceedings, volume 2019, page 228. American Medical Informatics Association, 2019.
  • [2] Richard F Averill and Rhonda R Butler. Misperceptions, misinformation, and misrepresentations: The icd-10-cm/pcssaga. Journal of AHIMA, 2013.
  • [3] Lauren B Ball, Steven C Macdonald, Joshua A Mott, and Ruth A Etzel. Carbon monoxide-related injury estimation using icd-coded data: methodologic implications for public health surveillance. Archives of Environmental & Occupational Health, 60(3):119–127, 2005.
  • [4] Tal Baumel, Jumana Nassour-Kassis, Raphael Cohen, Michael Elhadad, and Noemie Elhadad. Multi-label classification of patient notes a case study on icd code assignment. arXiv preprint arXiv:1709.09587, 2017.
  • [5] Curtis Benesch, DM Witter, AL Wilder, PW Duncan, GP Samsa, and DB Matchar. Inaccuracy of the international classification of diseases (icd-9-cm) in identifying the diagnosis of ischemic cerebrovascular disease. Neurology, 49(3):660–664, 1997.
  • [6] William R Best, Shukri F Khuri, Maureen Phelan, Kwan Hur, William G Henderson, John G Demakis, and Jennifer Daley. Identifying patient preoperative risk factors and postoperative adverse events in administrative databases: results from the department of veterans affairs national surgical quality improvement program. Journal of the American College of Surgeons, 194(3):257–266, 2002.
  • [7] Ankeet S Bhatt, Erin E McElrath, Brian L Claggett, Deepak L Bhatt, Dale S Adler, Scott D Solomon, and Muthiah Vaduganathan. Accuracy of icd-10 diagnostic codes to identify covid-19 among hospitalized patients. Journal of general internal medicine, 36(8):2532–2535, 2021.
  • [8] Panagiota Birmpili, Eleanor Atkins, Qiuju Li, Amundeep S Johal, Sam Waton, Robin Williams, Arun D Pherwani, and David A Cromwell. Evaluation of the icd-10 system in coding revascularisation procedures in patients with peripheral arterial disease in england: A retrospective cohort study using national administrative and clinical databases. EClinicalMedicine, 55, 2023.
  • [9] Donna Z Bliss, Laurie McNichol, Donna Cartwright, and Mikel Gray. Practice alert: new icd-10 codes for masd. Journal of Wound, Ostomy, and Continence Nursing, 49(1):15, 2022.
  • [10] Jacob Bodilsen, Steffen Leth, Stig Lønberg Nielsen, Jon Gitz Holler, Thomas Benfield, and Lars Haukali Omland. Positive predictive value of icd-10 diagnosis codes for covid-19. Clinical Epidemiology, pages 367–372, 2021.
  • [11] Taxiarchis Botsis, Gunnar Hartvigsen, Fei Chen, and Chunhua Weng. Secondary use of ehr: data quality issues and informatics opportunities. Summit on translational bioinformatics, 2010:1, 2010.
  • [12] Nele Brusselaers, Stan Monstrey, Dirk Vogelaers, Eric Hoste, and Stijn Blot. Severe burn injury in europe: a systematic review of the incidence, etiology, morbidity, and mortality. Critical care, 14(5):1–12, 2010.
  • [13] Li Cao and John E Morley. Sarcopenia is recognized as an independent condition by an international classification of disease, tenth revision, clinical modification (icd-10-cm) code. Journal of the American Medical Directors Association, 17 (8): 675–677, 2016.
  • [14] Donna J Cartwright. Icd-9-cm to icd-10-cm codes: what? why? how?, 2013.
  • [15] Finneas Catling, Georgios P Spithourakis, and Sebastian Riedel. Towards automated clinical coding. International journal of medical informatics, 120:50–61, 2018.
  • [16] Pei-Fu Chen, Ssu-Ming Wang, Wei-Chih Liao, Lu-Cheng Kuo, Kuan-Chih Chen, Yu-Cheng Lin, Chi-Yu Yang, Chi-Hao Chiu, Shu-Chih Chang, Feipei Lai, et al. Automatic icd-10 coding and training system: deep neural network based on supervised learning. JMIR Medical Informatics, 9(8):e23230, 2021.
  • [17] Abdelahad Chraibi, David Delerue, Julien Taillard, Ismat Chaib Draa, Regis Beuscart, Arnaud Hansske, et al. A deep learning framework for automated icd-10 coding. In MIE, pages 347–351, 2021.
  • [18] Jillian M Clark and Ruth Marshall. Utilising international statistical classification of diseases and related health conditions (icd)-10 australian modification classifications of “health conditions” to achieve population health surveillance in an australian spinal cord injury cohort. Spinal Cord, 60(8):746–756, 2022.
  • [19] William O Cleverley and James O Cleverley. Essentials of health care finance. Jones & Bartlett Learning, 2017.
  • [20] Linda B Cottler and Bridget F Grant. Characteristics of nosologically informative data sets that address key diagnostic issues facing the diagnostic and statistical manual of mental disorders, (dsm-v) and international classification of diseases, (icd-11) substance use disorders workgroups. Addiction, 101:161–169, 2006.
  • [21] Andrei Michael Dreyer. Using Transformers to assign ICD codes to medical notes. PhD thesis, University of Stellenbosch, 2023.
  • [22] Lærke Storgaard Duerlund, Shakil Shakar, Henrik Nielsen, and Jacob Bodilsen. Positive predictive value of the icd-10 diagnosis code for long-covid. Clinical epidemiology, pages 141–148, 2022.
  • [23] John Dumay and James Guthrie. Involuntary disclosure of intellectual capital: is it relevant? Journal of Intellectual Capital, 18(1):29–44, 2017.
  • [24] Swetha Duraiswamy, Amanda Ignacio, Janice Weinberg, Sabrina E Sanchez, David R Flum, Michael K Paasche-Orlow, Kelly M Kenzik, Jennifer F Tseng, and Frederick Thurston Drake. Comparative accuracy of icd-9 vs icd-10 codes for acute appendicitis. Journal of the American College of Surgeons, 234(3):377–383, 2022.
  • [25] Cathy A Eastwood, Danielle A Southern, Chelsea Doktorchik, Shahreen Khair, Denise Cullen, Alicia Boxill, Malgorzata Maciszewski, Lucia Otero Varela, William Ghali, Lori Moskal, et al. Training and experience of coding with the world health organization’s international classification of diseases, eleventh revision. Health Information Management Journal, 52 (2): 92–100, 2023.
  • [26] Thomas J Falen and Aaron Liberman. Learning to code with icd-9-cm for health information management and health services administration 2006. Lippincott Williams & Wilkins, 2005.
  • [27] Samah Jamal Fodeh, Brenda T Fenton, Rixin Wang, Melissa Skanderson, Hamada Altalib, Deena Kuruvilla, Emmanuelle Schindler, Sally Haskell, Cynthia Brandt, and Jason J Sico. Understanding headache classification coding within the veterans health administration using icd-9-cm and icd-10-cm in fiscal years 2014–2017. Plos one, 18(1):e0279163, 2023.
  • [28] Kin Wah Fung, Rachel Richesson, Michelle Smerek, Katherine C Pereira, Beverly B Green, Ashwin Patkar, Megan Clowse, Alan Bauck, and Olivier Bodenreider. Preparing for the icd-10-cm transition: automated methods for translating icd codes in clinical phenotype definitions. eGEMs, 4(1), 2016.
  • [29] Kin Wah Fung, Julia Xu, and Olivier Bodenreider. The new international classification of diseases 11th edition: a comparative analysis with icd-10 and icd-10-cm. Journal of the American Medical Informatics Association, 27 (5) : 738–746, 2020.
  • [30] Jennifer H Garvin and C C S RHIA. Evaluation of public health reporting using ICD-10-CM. In APHA Scientific Session and Event Listing, 2006.
  • [31] Mikel Gray, Donna Z Bliss, and Laurie McNichol. Moisture-associated skin damage: expanding and updating practice based on the newest icd-10-cm codes. Journal of Wound, Ostomy and Continence Nursing, 49(2):143–151, 2022.
  • [32] Adi V Gundlapalli, Amy M Lavery, Tegan K Boehmer, Michael J Beach, Henry T Walke, Paul D Sutton, and Robert N Anderson. Death certificate–based icd-10 diagnosis codes for covid-19 mortality surveillance—united states, january–december 2020. Morbidity and Mortality Weekly Report, 70(14):523, 2021.
  • [33] Yi Guo, Zhaoyi Chen, Ke Xu, Thomas J George, Yonghui Wu, William Hogan, Elizabeth A Shenkman, and Jiang Bian. International classification of diseases, tenth revision, clinical modification social determinants of health codes are poorly used in electronic health records. Medicine, 99(52), 2020.
  • [34] James E Harrison, Stefanie Weber, Robert Jakob, and Christopher G Chute. Icd-11: an international classification of diseases for the twenty-first century. BMC medical informatics and decision making, 21(6):1–10, 2021.
  • [35] Elias Hossain, Rajib Rana, Niall Higgins, Jeffrey Soar, Prabal Datta Barua, Anthony R Pisani, et al. Natural language processing in electronic health records in relation to healthcare decision-making: a systematic review. arXiv preprint arXiv:2306.12834, 2023.
  • [36] Stacy A Johnson, Emily A Signor, Katie L Lappe, Jianlin Shi, Stephen L Jenkins, Sara W Wikstrom, Rachel D Kroencke, David Hallowell, Aubrey E Jones, and Daniel M Witt. A comparison of natural language processing to icd-10 codes for identification and characterization of pulmonary embolism. Thrombosis Research, 203:190–195, 2021.
  • [37] Rajvir Kaur and Jeewani Anupama Ginige. Comparative analysis of algorithmic approaches for auto-coding with icd10-am and achi. Studies in health technology and informatics, 252:73–79, 2018.
  • [38] Rajvir Kaur, Jeewani Anupama Ginige, and Oliver Obst. A systematic literature review of automated icd coding and classification systems using discharge summaries. arXiv preprint arXiv:2107.10652, 2021.
  • [39] Rajvir Kaur, Jeewani Anupama Ginige, and Oliver Obst. Ai-based icd coding and classification approaches using discharge summaries: A systematic literature review. Expert Systems with Applications, page 118997, 2022.
  • [40] Ramakanth Kavuluru, Isaac Hands, Eric B Durbin, and Lisa Witt. Automatic extraction of icd-o-3 primary sites from cancer pathology reports. AMIA Summits on Translational Science Proceedings, 2013:112, 2013.
  • [41] Garrett Keim, Amanda O’Halloran, Martha Kienzle, Alexis Topjian, Robert Berg, Robert Sutton, Nadir Yehya, and Ryan Morgan. 259: Icd-10 switch decreased in-hospital cardiac arrest incidence: Concern for exposure misclassification. Critical Care Medicine, 51(1):114, 2023.
  • [42] Patrick L Kerr and Gavin Bryant. Use of icd-10 codes for human trafficking: analysis of data from a large, multisite clinical database in the united states. Public Health Reports, 137(1 suppl):83S–90S, 2022.
  • [43] Patricia Biller Krauskopf. Mtbc icd 9-10 and breathe2relax. The Journal for Nurse Practitioners, 13(8):e407–e408, 2017.
  • [44] Kristine E Lynch, Benjamin Viernes, Elise Gatsby, Scott L DuVall, Barbara E Jones, Tamara L Box, Craig Kreisler, and ´ Makoto Jones. Positive predictive value of covid-19 icd-10 diagnosis codes across calendar time and clinical setting. Clinical Epidemiology, pages 1011–1018, 2021.
  • [45] Andreas Maercker, Chris R Brewin, Richard A Bryant, Marylene Cloitre, Geoffrey M Reed, Mark van Ommeren, Asma Humayun, Lynne M Jones, Ashraf Kagee, Augusto E Llosa, et al. Proposals for mental disorders specifically associated with stress in the international classification of diseases-11. The Lancet, 381(9878):1683–1685, 2013.
  • [46] Jakir Hossain Bhuiyan Masud, Chiang Shun, Chen-Cheng Kuo, Md Mohaimenul Islam, Chih-Yang Yeh, Hsuan-Chia Yang, and Ming-Chin Lin. Deep-adca: Development and validation of deep learning model for automated diagnosis code assignment using clinical notes in electronic medical records. Journal of Personalized Medicine, 12(5):707, 2022.
  • [47] Laurie McNichol, Donna Z Bliss, and Mikel Gray. Moisture-associated skin damage: expanding practice based on the newest icd-10-cm codes for irritant contact dermatitis associated with digestive secretions and fecal or urinary effluent from an abdominal stoma or enterocutaneous fistula. Journal of Wound, Ostomy, and Continence Nursing, 49(3):235, 2022.
  • [48] Kimberly J O’malley, Karon F Cook, Matt D Price, Kimberly Raiford Wildes, John F Hurdle, and Carol M Ashton. Measuring diagnoses: Icd code accuracy. Health services research, 40(5p2):1620–1639, 2005.
  • [49] Emily R Pfaff, Charisse Madlock-Brown, John M Baratta, Abhishek Bhatia, Hannah Davis, Andrew Girvin, Elaine Hill, Elizabeth Kelly, Kristin Kostka, Johanna Loomba, et al. Coding long covid: characterizing a new disease through an icd-10 lens. BMC medicine, 21(1):1–13, 2023.
  • [50] Hude Quan, Vijaya Sundararajan, Patricia Halfon, Andrew Fong, Bernard Burnand, Jean-Christophe Luthi, L Duncan Saunders, Cynthia A Beck, Thomas E Feasby, and William A Ghali. Coding algorithms for defining comorbidities in icd-9-cm and icd-10 administrative data. Medical care, pages 1130–1139, 2005.
  • [51] Joao Vasco Santos, Ricardo Novo, Julio Souza, Fernando Lopes, and Alberto Freitas. Transition from icd-9-cm to icd-10- cm/pcs in portugal: An heterogeneous implementation with potential data implications. Health Information Management Journal, 52(2):128–131, 2023.
  • [52] Samuel F Sears and Jamie B Conti. Quality of life and psychological functioning of icd patients. Heart, 87(5):488–493, 2002.
  • [53] Ming-Jen Sheu, Fu-Weng Liang, Sheng-Tun Li, Chung-Yi Li, and Tsung-Hsueh Lu. Validity of icd-10-cm codes used to identify patients with chronic hepatitis b and c virus infection in administrative claims data from the taiwan national health insurance outpatient claims dataset. Clinical Epidemiology, pages 185–192, 2020.
  • [54] Aaron Sonabend, Winston Cai, Yuri Ahuja, Ashwin Ananthakrishnan, Zongqi Xia, Sheng Yu, and Chuan Hong. Automated icd coding via unsupervised knowledge integration (unite). International journal of medical informatics, 139 : 104135, 2020.
  • [55] Michael Subotin and Anthony Davis. A system for predicting icd-10-pcs codes from electronic health records. In Proceedings of bionlp 2014, pages 59–67, 2014.
  • [56] Michael Subotin and Anthony R Davis. A method for modeling co-occurrence propensity of clinical codes with application to icd-10-pcs auto-coding. Journal of the American Medical Informatics Association, 23(5):866–871, 2016.
  • [57] Vijaya Sundararajan, Hude Quan, Patricia Halfon, Kiyohide Fushimi, Jean-Christophe Luthi, Bernard Burnand, William A Ghali, and International Methodology Consortium for Coded Health Information (IMECCHI). Cross-national comparative performance of three versions of the icd-10 charlson index. Medical care, pages 1210–1215, 2007.
  • [58] Maxim Topaz, Leah Shafran-Topaz, and Kathryn H Bowles. Icd-9 to icd-10: evolution, revolution, and current debates in the united states. Perspectives in Health Information Management/AHIMA, American Health Information Management Association, 10(Spring), 2013.
  • [59] Zachary Tran, Arjun Verma, Taylor Wurdeman, Sigrid Burruss, Kaushik Mukherjee, and Peyman Benharash. Icd-10 based machine learning models outperform the trauma and injury severity score (triss) in survival prediction. Plos one, 17 (10): e0276624, 2022.
  • [60] Owen Trigueros, Alberto Blanco, Nuria Lebena, Arantza Casillas, and Alicia P ˜ erez. Explainable icd multi-label classification of ehrs in spanish with convolutional attention. International Journal of Medical Informatics, 157:104615, 2022.
  • [61] Micaelan Valesky, Michael V Genuardi, Rachel P Ogilvie, and Sanjay R Patel. 0447 assessing the performance of billing codes to identify patients with central sleep apnea from the electronic medical record. Sleep, 42:A180, 2019.
  • [62] Patrick Wu, Aliya Gifford, Xiangrui Meng, Xue Li, Harry Campbell, Tim Varley, Juan Zhao, Robert Carroll, Lisa Bastarache, Joshua C Denny, et al. Mapping icd-10 and icd-10-cm codes to phecodes: workflow development and initial evaluation. JMIR medical informatics, 7(4):e14325, 2019.
  • [63] Yifan Wu, Min Zeng, Zhihui Fei, Ying Yu, Fang-Xiang Wu, and Min Li. Kaicd: A knowledge attention-based deep learning framework for automatic icd coding. Neurocomputing, 469:376–383, 2022.
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  • [65] Jingqing Zhang, Atri Sharma, Luis Bolanos, Tong Li, Ashwani Tanwar, Vibhor Gupta, and Yike Guo. A scalable workflow to build machine learning classifiers with clinician-in-the-loop to identify patients in specific diseases. arXiv preprint arXiv:2205.08891, 2022.
  • [66] Shuai Zhao, Xiaolin Diao, Yun Xia, Yanni Huo, Meng Cui, Yuxin Wang, Jing Yuan, and Wei Zhao. Automated icd coding for coronary heart diseases by a deep learning method. Heliyon, 9(3), 2023.
Toplam 66 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Derin Öğrenme
Bölüm Reviews
Yazarlar

Ibrahım I. Alkhateeb Bu kişi benim 0009-0003-3037-509X

Kürşat Mustafa Karaoğlan 0000-0001-9830-7622

Hakan Kutucu 0000-0001-7144-7246

Yayımlanma Tarihi 2 Şubat 2024
Yayımlandığı Sayı Yıl 2023 Cilt: 1 Sayı: 1

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