Diagnostic evaluation of viral versus bacterial tonsillopharyngitis using an artificial intelligence mobile application and symptom questionnaire

Yıl 2023, Cilt: 14 Sayı: 50, 151 - 157, 30.12.2023

Yusuf Yeşil , Mustafa Altındiş , Hande Toptan , Elmas Pınar Kahraman Kılbaş , Onur Bircan , Ömer Özgür Bahri Elmas , Mehmet Köroğlu

https://doi.org/10.17944/interdiscip.1297115

Öz

Objective: In this study, it was aimed to distinguish bacterial/viral tonsillopharyngitis (TP) by scoring the symptom and throat images of pediatric patients with artificial intelligence-based mobile application.

Method: Fifty-one patients who applied to Sakarya University Training and Research Hospital, Department of Pediatrics and Diseases with acute tonsillopharyngitis were included. Samples were taken from patients and mouth/throat pictures were taken so that the tonsils and pharynx were clearly visible. In the microbiology laboratory, identification with culture/MALDI-TOF MS (Biomerieux, France) from the first samples, and nucleic acid isolation from the other for molecular tests were performed. Symptoms such as fatigue, sore throat, muscle pain, cough, sneezing, and runny nose were questioned from each patient on a scale of 1 to 5. By uploading the symptom results and throat pictures to the artificial intelligence application, it was aimed to distinguish bacterial/viral tonsillopharyngitis with the developed scoring system.

Results: Of the 51 samples included in the study, 21 were culture positive and 30 were negative. The artificial intelligence application was defined as 20 out of 21 culture-positive samples, 3 out of 30 culture-negative samples as bacterial tonsillopharyngitis (Sensitivity: 95.2%, specificity: 90%).

Conclusion: This study is one of the first to bring together the artificial intelligence application and microbiology. AI/scoring system may have a role to play in the diagnosis of bacterial vs viral TP, and in doing so may enable more appropriate antibiotic usage targeted to only bacterial TP infections. It is important to distinguish between bacterial and viral tonsillopharyngitis in the COVID-19 pandemic.

Anahtar Kelimeler

Artificial Intelligence, Tonsillopharyngitis, Virus, Rational Antibiotic Use

Kaynakça

• National Comprehensive Cancer Network (NCCN 2.2015). NCCN Clinical practice guidelines in oncology. Available at: http://www.nccn.org/professionals/physician_gls/f_guidelines.asp. Accessed December 13, 2022.
• Wirth A, Yuen K, Barton M, Roos D, Gogna K, Pratt G, et al. Long-term outcome after radiotherapy alone for lymphocyte-predominant Hodgkin lymphoma: a retrospective multicenter study of the Australasian Radiation Oncology Lymphoma Group. Cancer 2005;104:1221. https://doi.org/10.1002/cncr.21303
• Centor RM, Witherspoon JM, Dalton HP, Brody CE, Link K. The diagnosis of strep throat in adults in the emergency room. Med Decis Making 1981;1:239-46. https://doi.org/10.1177/0272989X8100100304
• McIsaac WJ, White D, Tannenbaum D, Low DE. A clinical score to reduce unnecessary antibiotic use in patients with sore throat. CMAJ 1998;158:75-83.
• Bisno AL, Gerber MA, Gwaltney JM, Kaplan EL, Schwartz RH. Infectious Diseases Society of America. Practice guidelines for the diagnosis and management of group A streptococcal pharyngitis. Clin Infect Dis 2002;35:113-25. https://doi.org/10.1086/340949
• McCarthy J. What is artificial intelligence? Computer Sci- ence Department, Stanford University. Available at: http://www-formal.stanford.edu/jmc/whatisai.pdf. Accessed October 10, 2020.
• Nabiyev VV. Yapay zeka/artificial intelligence. Ankara, Seckin Yayinlari; 2003: 35-40.
• Begley RJ, Riege M, Rosenblum J, Tseng D. Adding intelligence to medical devices. Medical Device & Diagnostic Industry Magazine 2000;3:150.
• Industrial application of fuzzy logic control. Available at: http://www.fuzzytech.com/. Accessed October 10, 2020.
• Atici E. The Concept of Patient-Physician Relationship. Uludag Universitesi Tip Fak Derg 2007;33:45-50.
• Celebi ARC, Bektaş B, Ankaralı H, Yeşıl Y, Yüksel C, Karasu B, Özgür Ö, Tunç U. Diyabetik Retinopatide Farklı Makine Öğrenmesi Tekniklerinin Kullanımı ile Tanı Koymadaki Doğruluk Ölçütlerinin Karşılaştırılması. Tepecik Eğitim ve Araştırma Hastanesi Dergisi, Kongre Özel Sayısı 2020;30:64-66.
• Rosebrock A. Detecting COVID-19 in X-ray Images with Keras, TensorFlow, and Deep Learning. PyImageSearch, 16 March, 2020.
• Maghdid H, Ghafoor K, Sadiq A, Curran K, Rabie K. A Novel AI-enabled Framework to Diagnose Coronavirus COVID-19 using Smartphone Embedded Sensors: Design Study. ArXiv, https://arxiv.org/abs/2003.07434. Accessed October 15, 2022.
• Im H, Pathania D, McFarland PJ, Sohani AR, Degani I, Allen M, et al. Design and clinical validation of a point-of-care device for the diagnosis of lymphoma via contrast-enhanced microholography and machine learning. Nat Biomed Eng 2018;2:666-674. https://doi.org/10.1038/s41551-018-0265-3
• Chen JH, Asch SM. Machine learning and prediction in medicine-beyond the peak of inflated expectations. N Engl J Med 2017;376:2507-2509. https://doi.org/10.1056/NEJMp1702071
• Boon IS, Yong TPTA, Boon CS. Assessing the role of artificial intelligence (AI) in clinical oncology: utility of machine learning in radiotherapy target volume delineation. Medicines (Basel) 2018;5:E131. https://doi.org/10.3390/medicines5040131
• Sun G, Matsui T, Hakozaki Y, Abe S. An infectious disease/fever screening radar system which stratifies higher-risk patients within ten seconds using a neural network and the fuzzy grouping method. J Infect 2015;70:230-236. https://doi.org/10.1016/j.jinf.2014.12.007
• Saybani MR, Shamshirband S, Golzari S, Wah TY, Saeed A, Mat Kiah ML, et al. RAIRS2 a new expert system for diagnosing tuberculosis with real-world tournament selection mechanism inside artificial immune recognition system. Med Biol Eng Comput 2016;54:385. https://doi.org/10.1007/s11517-015-1323-6
• Babalik A, Guler I. Boğaz enfeksiyonlarının teşhis ve tedavisinde uzman sistem kullanımı. Selçuk Teknik Dergisi 2007;6:109-119.
• Leelasantitham A, Kiattisin S. A diagnosis of tonsillitis using image processing and neural network. International Journal of Applied Biomedical Engineering 2009;2:36-42.
• Altindis M, Elmas B, Kilic U, Aslan FG, Kucukkkara G, Koroglu M. Loop-Mediated Isothermal Amplifi cation PCR (LAMP-PCR) For Rapid Molecular Diagnosis of Group A Streptococci. J Biotechinol & Strategic Health Res 2017;1:11-16.