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Current Artificial Intelligence Applications in Vertigo: A Review

Yıl 2025, Cilt: 35 Sayı: 1, 47 - 58, 28.03.2025

Ümit Duman , Ayşe Defne Orhan , Vedat Güneş , Elif Kocasoy Orhan

https://doi.org/10.26650/Tr-ENT.2025.1644509

Öz

Vertigo and dizziness symptoms affect approximately 20% of the population. With the increasing use of artificial intelligence (AI) in healthcare, AI applications have been developed to assess "vertigo and dizziness." A common approach in evaluating patients with these symptoms is to analyse the vestibule ocular reflex (VOR). A review of the literature shows that data such as nystagmus evaluations, vestibular test results, and patient history are processed through AI methods-particularly deep learning models —to analyse data from patients experiencing dizziness. This study reviews current AI applications and outcomes in the field of vertigo and dizziness. The goal is to provide a summary of the studies and offer guidance for future research on the use of machine learning and AI in vertigo diagnosis. The appli cations being developed will streamline the differentiation between the central and peripheral causes of vestibular symptoms in high-demand areas such as neurology and otorhinolaryngology emergency departments. These advancements will enable more accurate and timely referrals and simplify vestibular assessments in audiology, otorhinolaryngology, and neurology clinics.

Anahtar Kelimeler

Artificial intelligence machine learning vestibular vertigo dizziness

Kaynakça

  • Baloh RW, Hunrubai V, Kerber KA. Overview of vestibular anatomY and phYsiologY. In: Baloh RW, Hunrubai V, Kerber KA. Baloh and Honrubia's clinical neurophYsiologY of the vestibular sYstem. 4 edition. Oxford: Oxford UniversitY Press, 2010.p.2-24. google scholar
  • DiPietro MA, Ung RL. EmergencY department evaluation of vertigo and dizziness. EmergencY Medicine Report. MaY 2023. https://www.reliasmedia. com/articles/emergencY-department-evaluation-of-vertigo-and-dizziness. google scholar
  • Bisdorff A, Von Brevern M, Lempert T, Newman-Toker DE. Classification of vestibular sYmptoms: towards an international classification of vestibular disorders. J Vestib Res 2009;19(1-2):1-13. google scholar
  • von Brevern M, Bertholon P, Brandt T, Fife T, Imai T, Nuti D, et al. Benign paroxYsmal positional vertigo: Diagnostic criteria Consensus document of the Committee for the Classification of Vestibular Disorders of the BârânY Society. Acta Otorrinolaringol Esp (Engl Ed) 2017;68(6):349-60. google scholar
  • Lopez-Escamez JA, Carey J, Chung WH, Goebel JA, Magnusson M, Mandala M, et al. Diagnostic criteria for Meniere's disease according to the Classification Committee of the Bârâny Society. HNO 2017;65(ll):887-93. google scholar
  • Strupp M, Bisdorff A, Furman J, Hornibrook J, Jahn K, Maire R, et al. Acute unilateral vestibulopathY/vestibular neuritis: Diagnostic criteria. J Vestib Res 2022;32(5):389-406. google scholar
  • Lempert T, Olesen J, Furman J, Waterston J, Seemungal B, CareY J, et al. Vestibular migraine: Diagnostic criteria1. J Vestib Res 2022;32(1):1-6. google scholar
  • Rastall DP, Green K. Deep learning in acute vertigo diagnosis. J Neurol Sci 2022;443:120454. google scholar
  • Wikipedia. Artificial intelligence. 2024. https://en.wikipedia.org/w/index.php? title=Artificial_intelligence&oldid=1219595774. google scholar
  • Guo Y, Hao Z, Zhao S, Gong J, Yang F. Artificial Intelligence in Health Care: Bibliometric AnalYsis. J Med Internet Res 2020;22(7):e18228. google scholar
  • Kononenko I. Machine learning for medical diagnosis: historY, state of the art and perspective. Artif Intell Med 2001;23(1):89-109. google scholar
  • Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng 2018;2(10):719-31. google scholar
  • ReddY S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare deliverY. J R Soc Med 2019;112(1):22-8. google scholar
  • Lee Y, Lee S, Han J, Seo YJ, Yang S. A nYstagmus extraction sYstem using artificial intelligence for video-nYstagmographY. Sci Rep 2023;13(1):11975. google scholar
  • Lim EC, Park JH, Jeon HJ, Kim HJ, Lee HJ, Song CG, et al. Developing a diagnostic decision support sYstem for benign paroxYsmal positional vertigo using a deep-learning model. J Clin Med 2019;8(5):633. google scholar
  • Wu P, Liu X, Dai Q, Yu J, Zhao J, Yu F, et al. Diagnosing the benign paroxYsmal positional vertigo via 1D and deep-learning composite model. J Neurol 2023;270(8):3800-9. google scholar
  • Microsoft. Azure Machine Learning: Advanced Machine Learning with AutoML. December 24, 2024. https://azure.microsoft.com/en-us/services/machine-learning/. google scholar
  • Google. TensorFlow Lite: machine learning on edge devices. December 24, 2024 https://www.tensorflow.org/lite. google scholar
  • Google. Albumentations: Fast and flexible ımage augmentations. December 24, 2024 https://albumentations.ai/. google scholar
  • OpenAl. CLIP: Contrastive Language-lmage Pretraining. December 24, 2024 https://openai.com/research/clip. google scholar
  • Groezinger M, Huppert D, Strobl R, Grill E. Development and validation of a classification algorithm to diagnose and differentiate spontaneous episodic vertigo sYndromes: results from the DizzYReg patient registrY. J Neurol 2020;267(Suppl 1):160-7. google scholar
  • Lim E-C, Park JH, Jeon HJ, Kim H-J, Lee H-J, Song C-G, et al. Developing a diagnostic decision support sYstem for benign paroxYsmal positional vertigo using a deep-learning model. J Clin Med 2019;8(5):633. google scholar
  • Wang C, Young AS, Raj C, Bradshaw AP, Nham B, Rosengren SM, et al. Machine learning models help differentiate between causes of recurrent spontaneous vertigo. J Neurol 2024;271(6):3426-38. google scholar
  • Kentala E, PYYkkö I, Auramo Y, Laurikkala J, Juhola M. Otoneurological expert sYstem for vertigo. Acta OtolarYngol 1999;119(5):517-21. google scholar
  • Kabade V, Hooda R, Raj C, Awan Z, Young AS, Welgampola MS, et al. machine learning techniques for differential diagnosis of vertigo and dizziness: A review. Sensors 2021;21(22):7565. google scholar
  • Chee J, Kwa ED, Goh X. "Vertigo, likelY peripheral": The dizzYing rise of ChatGPT. Eur Arch OtorhinolarYngol 2023;280(10):4687-9. google scholar
  • Lin SC, Lin MY, Kang BH, Lin YS, Liu YH, Yin CY, et al. Artificial neural network-assisted classification of hearing prognosis of sudden sensorineural hearing loss with vertigo. IEEE J Transl Eng Health Med 2023;11:170-81. google scholar
  • Bansal M. Clinical Evaluation of 'Computer-Aided Diagnosis InNeuro-OtologY (CADINO)' in terms of usefulness, functionalitY and effectiveness. Indian J OtolarYngol Head Neck Surg 2022;74(Suppl 3):4434-40. google scholar
  • Ahmadi S-A, Vivar G, Navab N, Möhwald K, Maier A, Hadzhikolev H, et al. Modern machine-learning can support diagnostic differentiation of central and peripheral acute vestibular disorders. J Neurol 2020;267(1):143-52. google scholar
  • Visscher RMS, Feddermann-Demont N, Romano F, Straumann D, Bertolini G. Artificial intelligence for understanding concussion: Retrospective cluster analYsis on the balance and vestibular diagnostic data of concussion patients. PLoS One 2019;14(4):e0214525. google scholar
  • Luo J, Erbe C, Friedland DR. Unique Clinical language patterns among expert vestibular providers can predict vestibular diagnoses. Otol Neurotol 2018;39(9):1163-71. google scholar
  • Richburg HA, Povinelli RJ, Friedland DR, editors. Direct-to-Patient SurveY for Diagnosis of Benign ParoxYsmal Positional Vertigo. 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA); 2018 17-20 Dec. 2018. google scholar
  • Ben Slama A, Mouelhi A, Sahli H, Manoubi S, Mbarek C, Trabelsi H, et al. A new preprocessing parameter estimation based on geodesic active contour model for automatic vestibular neuritis diagnosis. Artif Intell Med 2017;80:48-62. google scholar
  • HeYdarov S, İkizoğlu S, Şahin K, Kara E, Çakar T, Ataş A. Performance comparison of ML methods applied to motion sensorY information for identification of vestibular sYstem disorders. 2017 10th International Conference on Electrical and Electronics Engineering (ELECO); 2017 30 Nov.-2 Dec. 2017. google scholar
  • Priesol AJ, Cao M, BrodleY CE, Lewis RF. Clinical vestibular testing assessed with machine-learning algorithms. JAMA OtolarYngol Head Neck Surg 2015;141(4):364-72. google scholar
  • Adelsberger R, Valko Y, Straumann D, Tröster G. Automated Romberg testing in patients with benign paroxysmal positional vertigo and healthy subjects. IEEE Trans Biomed Eng 2015;62(1):373-81. google scholar
  • Dong C, Wang Y, Zhang Q, Wang N. The methodology of Dynamic Uncertain Causality Graph for intelligent diagnosis of vertigo. Comput Methods Programs Biomed 2014;113(1):162-74. google scholar
  • Miettinen K, Juhola M. Classification of otoneurological cases according to bayesian probabilistic models. J Med Syst 2010;34(2):119-30. google scholar
  • Varpa K, Iltanen K, Juhola M. Machine learning method for knowledge discovery experimented with otoneurological data. Comput Methods Programs Biomed 2008;91(2):154-64. google scholar
  • Juhola M, Aalto H, Hirvonen T. Machine learning recognition of otoneurological patients by means of the results of vestibulo-ocular signal analysis. 2008 21st IEEE International Symposium on Computer-Based Medical Systems; 2008 17-19 June 2008. google scholar
  • Figueira LB, Neto LP, Bertini JR, Nicoletti MC. Using constructive neural networks for detecting central vestibular system lesion. Applied Artificial Intelligence 2006;20(7):609-38. google scholar
  • Tossavainen T, Toppila E, Pyykko I, Forsman PM, Juhola M, Starck J. Virtual reality in posturography. IEEE Trans Inf Technol Biomed 2006;10(2):282-92. google scholar
  • Kohigashi S, Nakamae K, Fujioka H. Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo: SPIE; 2005. google scholar
  • Juhola M, Viikki K, Laurikkala J, Auramo Y, Kentala E, Pyykkö I. Application of artificial intelligence in audiology. Scand Audiol Suppl 2001(52):97-9. google scholar
  • Sandeep Ganesh G, Kolusu AS, Prasad K, Samudrala PK, Nemmani KVS. Advancing health care via artificial intelligence: From concept to clinic. Eur J Pharmacol 2022;934:175320. google scholar
  • U.S. Food & Drug Administration. Artificial ıntelligence and machine learning in software as a medical device medical devices. December 30, 2024. https://www.fda.gov/medical-devices/software-medical-device-samd/ artificial-intelligence-and-machine-learning-software-medical-device. google scholar
  • Çamur E, Cesur T, Güneş YC. A comparative study: performance of large language models in simplifying turkish computed tomography reports. J Ist Faculty Med 2024;87(4):321-6. google scholar

Yıl 2025, Cilt: 35 Sayı: 1, 47 - 58, 28.03.2025

Ümit Duman , Ayşe Defne Orhan , Vedat Güneş , Elif Kocasoy Orhan

https://doi.org/10.26650/Tr-ENT.2025.1644509

Öz

Kaynakça

  • Baloh RW, Hunrubai V, Kerber KA. Overview of vestibular anatomY and phYsiologY. In: Baloh RW, Hunrubai V, Kerber KA. Baloh and Honrubia's clinical neurophYsiologY of the vestibular sYstem. 4 edition. Oxford: Oxford UniversitY Press, 2010.p.2-24. google scholar
  • DiPietro MA, Ung RL. EmergencY department evaluation of vertigo and dizziness. EmergencY Medicine Report. MaY 2023. https://www.reliasmedia. com/articles/emergencY-department-evaluation-of-vertigo-and-dizziness. google scholar
  • Bisdorff A, Von Brevern M, Lempert T, Newman-Toker DE. Classification of vestibular sYmptoms: towards an international classification of vestibular disorders. J Vestib Res 2009;19(1-2):1-13. google scholar
  • von Brevern M, Bertholon P, Brandt T, Fife T, Imai T, Nuti D, et al. Benign paroxYsmal positional vertigo: Diagnostic criteria Consensus document of the Committee for the Classification of Vestibular Disorders of the BârânY Society. Acta Otorrinolaringol Esp (Engl Ed) 2017;68(6):349-60. google scholar
  • Lopez-Escamez JA, Carey J, Chung WH, Goebel JA, Magnusson M, Mandala M, et al. Diagnostic criteria for Meniere's disease according to the Classification Committee of the Bârâny Society. HNO 2017;65(ll):887-93. google scholar
  • Strupp M, Bisdorff A, Furman J, Hornibrook J, Jahn K, Maire R, et al. Acute unilateral vestibulopathY/vestibular neuritis: Diagnostic criteria. J Vestib Res 2022;32(5):389-406. google scholar
  • Lempert T, Olesen J, Furman J, Waterston J, Seemungal B, CareY J, et al. Vestibular migraine: Diagnostic criteria1. J Vestib Res 2022;32(1):1-6. google scholar
  • Rastall DP, Green K. Deep learning in acute vertigo diagnosis. J Neurol Sci 2022;443:120454. google scholar
  • Wikipedia. Artificial intelligence. 2024. https://en.wikipedia.org/w/index.php? title=Artificial_intelligence&oldid=1219595774. google scholar
  • Guo Y, Hao Z, Zhao S, Gong J, Yang F. Artificial Intelligence in Health Care: Bibliometric AnalYsis. J Med Internet Res 2020;22(7):e18228. google scholar
  • Kononenko I. Machine learning for medical diagnosis: historY, state of the art and perspective. Artif Intell Med 2001;23(1):89-109. google scholar
  • Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng 2018;2(10):719-31. google scholar
  • ReddY S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare deliverY. J R Soc Med 2019;112(1):22-8. google scholar
  • Lee Y, Lee S, Han J, Seo YJ, Yang S. A nYstagmus extraction sYstem using artificial intelligence for video-nYstagmographY. Sci Rep 2023;13(1):11975. google scholar
  • Lim EC, Park JH, Jeon HJ, Kim HJ, Lee HJ, Song CG, et al. Developing a diagnostic decision support sYstem for benign paroxYsmal positional vertigo using a deep-learning model. J Clin Med 2019;8(5):633. google scholar
  • Wu P, Liu X, Dai Q, Yu J, Zhao J, Yu F, et al. Diagnosing the benign paroxYsmal positional vertigo via 1D and deep-learning composite model. J Neurol 2023;270(8):3800-9. google scholar
  • Microsoft. Azure Machine Learning: Advanced Machine Learning with AutoML. December 24, 2024. https://azure.microsoft.com/en-us/services/machine-learning/. google scholar
  • Google. TensorFlow Lite: machine learning on edge devices. December 24, 2024 https://www.tensorflow.org/lite. google scholar
  • Google. Albumentations: Fast and flexible ımage augmentations. December 24, 2024 https://albumentations.ai/. google scholar
  • OpenAl. CLIP: Contrastive Language-lmage Pretraining. December 24, 2024 https://openai.com/research/clip. google scholar
  • Groezinger M, Huppert D, Strobl R, Grill E. Development and validation of a classification algorithm to diagnose and differentiate spontaneous episodic vertigo sYndromes: results from the DizzYReg patient registrY. J Neurol 2020;267(Suppl 1):160-7. google scholar
  • Lim E-C, Park JH, Jeon HJ, Kim H-J, Lee H-J, Song C-G, et al. Developing a diagnostic decision support sYstem for benign paroxYsmal positional vertigo using a deep-learning model. J Clin Med 2019;8(5):633. google scholar
  • Wang C, Young AS, Raj C, Bradshaw AP, Nham B, Rosengren SM, et al. Machine learning models help differentiate between causes of recurrent spontaneous vertigo. J Neurol 2024;271(6):3426-38. google scholar
  • Kentala E, PYYkkö I, Auramo Y, Laurikkala J, Juhola M. Otoneurological expert sYstem for vertigo. Acta OtolarYngol 1999;119(5):517-21. google scholar
  • Kabade V, Hooda R, Raj C, Awan Z, Young AS, Welgampola MS, et al. machine learning techniques for differential diagnosis of vertigo and dizziness: A review. Sensors 2021;21(22):7565. google scholar
  • Chee J, Kwa ED, Goh X. "Vertigo, likelY peripheral": The dizzYing rise of ChatGPT. Eur Arch OtorhinolarYngol 2023;280(10):4687-9. google scholar
  • Lin SC, Lin MY, Kang BH, Lin YS, Liu YH, Yin CY, et al. Artificial neural network-assisted classification of hearing prognosis of sudden sensorineural hearing loss with vertigo. IEEE J Transl Eng Health Med 2023;11:170-81. google scholar
  • Bansal M. Clinical Evaluation of 'Computer-Aided Diagnosis InNeuro-OtologY (CADINO)' in terms of usefulness, functionalitY and effectiveness. Indian J OtolarYngol Head Neck Surg 2022;74(Suppl 3):4434-40. google scholar
  • Ahmadi S-A, Vivar G, Navab N, Möhwald K, Maier A, Hadzhikolev H, et al. Modern machine-learning can support diagnostic differentiation of central and peripheral acute vestibular disorders. J Neurol 2020;267(1):143-52. google scholar
  • Visscher RMS, Feddermann-Demont N, Romano F, Straumann D, Bertolini G. Artificial intelligence for understanding concussion: Retrospective cluster analYsis on the balance and vestibular diagnostic data of concussion patients. PLoS One 2019;14(4):e0214525. google scholar
  • Luo J, Erbe C, Friedland DR. Unique Clinical language patterns among expert vestibular providers can predict vestibular diagnoses. Otol Neurotol 2018;39(9):1163-71. google scholar
  • Richburg HA, Povinelli RJ, Friedland DR, editors. Direct-to-Patient SurveY for Diagnosis of Benign ParoxYsmal Positional Vertigo. 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA); 2018 17-20 Dec. 2018. google scholar
  • Ben Slama A, Mouelhi A, Sahli H, Manoubi S, Mbarek C, Trabelsi H, et al. A new preprocessing parameter estimation based on geodesic active contour model for automatic vestibular neuritis diagnosis. Artif Intell Med 2017;80:48-62. google scholar
  • HeYdarov S, İkizoğlu S, Şahin K, Kara E, Çakar T, Ataş A. Performance comparison of ML methods applied to motion sensorY information for identification of vestibular sYstem disorders. 2017 10th International Conference on Electrical and Electronics Engineering (ELECO); 2017 30 Nov.-2 Dec. 2017. google scholar
  • Priesol AJ, Cao M, BrodleY CE, Lewis RF. Clinical vestibular testing assessed with machine-learning algorithms. JAMA OtolarYngol Head Neck Surg 2015;141(4):364-72. google scholar
  • Adelsberger R, Valko Y, Straumann D, Tröster G. Automated Romberg testing in patients with benign paroxysmal positional vertigo and healthy subjects. IEEE Trans Biomed Eng 2015;62(1):373-81. google scholar
  • Dong C, Wang Y, Zhang Q, Wang N. The methodology of Dynamic Uncertain Causality Graph for intelligent diagnosis of vertigo. Comput Methods Programs Biomed 2014;113(1):162-74. google scholar
  • Miettinen K, Juhola M. Classification of otoneurological cases according to bayesian probabilistic models. J Med Syst 2010;34(2):119-30. google scholar
  • Varpa K, Iltanen K, Juhola M. Machine learning method for knowledge discovery experimented with otoneurological data. Comput Methods Programs Biomed 2008;91(2):154-64. google scholar
  • Juhola M, Aalto H, Hirvonen T. Machine learning recognition of otoneurological patients by means of the results of vestibulo-ocular signal analysis. 2008 21st IEEE International Symposium on Computer-Based Medical Systems; 2008 17-19 June 2008. google scholar
  • Figueira LB, Neto LP, Bertini JR, Nicoletti MC. Using constructive neural networks for detecting central vestibular system lesion. Applied Artificial Intelligence 2006;20(7):609-38. google scholar
  • Tossavainen T, Toppila E, Pyykko I, Forsman PM, Juhola M, Starck J. Virtual reality in posturography. IEEE Trans Inf Technol Biomed 2006;10(2):282-92. google scholar
  • Kohigashi S, Nakamae K, Fujioka H. Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo: SPIE; 2005. google scholar
  • Juhola M, Viikki K, Laurikkala J, Auramo Y, Kentala E, Pyykkö I. Application of artificial intelligence in audiology. Scand Audiol Suppl 2001(52):97-9. google scholar
  • Sandeep Ganesh G, Kolusu AS, Prasad K, Samudrala PK, Nemmani KVS. Advancing health care via artificial intelligence: From concept to clinic. Eur J Pharmacol 2022;934:175320. google scholar
  • U.S. Food & Drug Administration. Artificial ıntelligence and machine learning in software as a medical device medical devices. December 30, 2024. https://www.fda.gov/medical-devices/software-medical-device-samd/ artificial-intelligence-and-machine-learning-software-medical-device. google scholar
  • Çamur E, Cesur T, Güneş YC. A comparative study: performance of large language models in simplifying turkish computed tomography reports. J Ist Faculty Med 2024;87(4):321-6. google scholar
Toplam 47 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Kulak Burun Boğaz, Klinik Tıp Bilimleri (Diğer)
Bölüm Derlemeler
Yazarlar

Ümit Duman 0000-0001-8978-3563

Ayşe Defne Orhan 0009-0000-2286-9629

Vedat Güneş 0000-0002-5665-5909

Elif Kocasoy Orhan 0000-0002-2110-4832

Yayımlanma Tarihi 28 Mart 2025
Gönderilme Tarihi 21 Şubat 2025
Kabul Tarihi 11 Mart 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 35 Sayı: 1

Kaynak Göster

APA Duman, Ü., Orhan, A. D., Güneş, V., Kocasoy Orhan, E. (2025). Current Artificial Intelligence Applications in Vertigo: A Review. The Turkish Journal of Ear Nose and Throat, 35(1), 47-58. https://doi.org/10.26650/Tr-ENT.2025.1644509
AMA Duman Ü, Orhan AD, Güneş V, Kocasoy Orhan E. Current Artificial Intelligence Applications in Vertigo: A Review. Tr-ENT. Mart 2025;35(1):47-58. doi:10.26650/Tr-ENT.2025.1644509
Chicago Duman, Ümit, Ayşe Defne Orhan, Vedat Güneş, ve Elif Kocasoy Orhan. “Current Artificial Intelligence Applications in Vertigo: A Review”. The Turkish Journal of Ear Nose and Throat 35, sy. 1 (Mart 2025): 47-58. https://doi.org/10.26650/Tr-ENT.2025.1644509.
EndNote Duman Ü, Orhan AD, Güneş V, Kocasoy Orhan E (01 Mart 2025) Current Artificial Intelligence Applications in Vertigo: A Review. The Turkish Journal of Ear Nose and Throat 35 1 47–58.
IEEE Ü. Duman, A. D. Orhan, V. Güneş, ve E. Kocasoy Orhan, “Current Artificial Intelligence Applications in Vertigo: A Review”, Tr-ENT, c. 35, sy. 1, ss. 47–58, 2025, doi: 10.26650/Tr-ENT.2025.1644509.
ISNAD Duman, Ümit vd. “Current Artificial Intelligence Applications in Vertigo: A Review”. The Turkish Journal of Ear Nose and Throat 35/1 (Mart 2025), 47-58. https://doi.org/10.26650/Tr-ENT.2025.1644509.
JAMA Duman Ü, Orhan AD, Güneş V, Kocasoy Orhan E. Current Artificial Intelligence Applications in Vertigo: A Review. Tr-ENT. 2025;35:47–58.
MLA Duman, Ümit vd. “Current Artificial Intelligence Applications in Vertigo: A Review”. The Turkish Journal of Ear Nose and Throat, c. 35, sy. 1, 2025, ss. 47-58, doi:10.26650/Tr-ENT.2025.1644509.
Vancouver Duman Ü, Orhan AD, Güneş V, Kocasoy Orhan E. Current Artificial Intelligence Applications in Vertigo: A Review. Tr-ENT. 2025;35(1):47-58.
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