Exploring the Potential of Artificial Intelligence in Infectious Disease

Abstract

Artificial intelligence (AI) addressed several infectious disease concerns by using its capabilities and acknowledging its constraints, with some adjustments and clarifications. The research focused on important difficulties related to artificial intelligence in infectious diseases. This review advocates for the use of artificial intelligence in infectious disease clinical practice and research. AI categorises article components such as title, abstract, introduction, method, findings, and discussions, which helps scholars save time. This speeds up and improves scientific writing. Some comments may be misleading or inaccurate, putting the accuracy of the research at risk. Current AI systems provide precise and safe responses, but they often lack contextual understanding. The lack of diagnostic technologies in artificial intelligence leads to misidentification and safety risks. Utilising medical technology ethically requires supervision and regulation. Some institutions have prohibited AI research because of its inefficacy. AI may assist physicians by gathering medical data and patient case studies. Identify and control new technologies. ChatGPT and other medical AI models need more data for training.

Keywords

• Artificial intelligence
• ChatGPT
• Infectious disease

Bulaşıcı Hastalıklarda Yapay Zeka Potansiyelinin Keşfedilmesi

Abstract

Yapay zeka (YZ), yeteneklerini kullanarak ve kısıtlamalarını kabul ederek, bazı ayarlamalar ve açıklamalarla çeşitli bulaşıcı hastalık endişelerini ele aldı. Araştırma, bulaşıcı hastalıklarda YZ ile ilgili önemli zorluklara odaklanmıştır. Bu derleme, bulaşıcı hastalıkların klinik uygulamalarında ve araştırmalarında yapay zekânın kullanılmasını savunmaktadır. YZ; başlık, özet, giriş, yöntem, bulgular ve tartışmalar gibi makale bileşenlerini kategorize ederek akademisyenlerin zamandan tasarruf etmesine yardımcı oluyor. Bu da bilimsel yazımı hızlandırır ve geliştirir. Bazı yorumlar yanıltıcı veya yanlış olabilir ve araştırmanın doğruluğunu riske atabilir. Mevcut YZ sistemleri kesin ve güvenli yanıtlar veriyor, ancak genellikle bağlamsal anlayıştan yoksunlar. YZ’ de teşhis teknolojilerinin eksikliği, yanlış tanımlama ve güvenlik risklerine yol açmaktadır. Tıbbi teknolojinin etik olarak kullanılması denetim ve düzenleme gerektirir. Bazı kurumlar, etkisizliği nedeniyleYZ araştırmalarını yasaklamıştır. YZ, tıbbi verileri ve hasta vaka çalışmalarını toplayarak hekimlere yardımcı olabilir. Yeni teknolojileri tanımlayın ve kontrol edin. ChatGPT ve diğer tıbbi YZ modellerinin eğitim için daha fazla veriye ihtiyacı vardır.

Keywords

• Yapay zeka
• ChatGPT
• Bulaşıcı hastalıklar

References

1. 1. Brownstein JS, Rader B, Astley CM, et al. Advances in Artificial Intelligence for Infectious-Disease Surveillance. N Engl J Med 2023;388:1597-607.
2. 2. Smith KP, Kirby JE. Image analysis and artificial intelligence in infectious disease diagnostics. Clin Microbiol Infect 2020;26:1318-23.
3. 3. Wong F, de la Fuente-Nunez C, Collins JJ. Leveraging artificial intelligence in the fight against infectious diseases. Science 2023;381:164-70.
4. 4. Chu WT, Reza SMS, Anibal JT, et al. Artificial Intelligence and Infectious Disease Imaging. J Infect Dis 2023;228:322-36.
5. 5. Schwalbe N, Wahl B. Artificial intelligence and the future of global health. Lancet 2020;395:1579-86.
6. 6. Shi L, Zhang JF, Li W, et al. [Artificial intelligence facilitates tropical infectious disease control and research]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2022;34:445-52.
7. 7. Wong ZSY, Zhou J, Zhang Q. Artificial Intelligence for infectious disease Big Data Analytics. Infect Dis Health 2019;24:44-8.
8. 8. Cheng K, Li Z, He Y, et al. Potential Use of Artificial Intelligence in Infectious Disease: Take ChatGPT as an Example. Ann Biomed Eng 2023;51:1130-5.

9. 9. Parums DV. Editorial: Infectious Disease Surveillance Using Artificial Intelligence (AI) and its Role in Epidemic and Pandemic Preparedness. Med Sci Monit 2023;29:e941209.
10. 10. Relf MV. Artificial Intelligence and Scientific Publishing. J Assoc Nurses AIDS Care 2023;34:329-30.
11. 11. Siddig EE, Eltigani HF, Ahmed A. The Rise of AI: How Artificial Intelligence is Revolutionizing Infectious Disease Control. Ann Biomed Eng 2023;51:2636-7.
12. 12. Peiffer-Smadja N, Rawson TM, Ahmad R, et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect 2020;26:584-95.
13. 13. Tran NK, Albahra S, May L, et al. Evolving Applications of Artificial Intelligence and Machine Learning in Infectious Diseases Testing. Clin Chem 2021;68:125-33.
14. 14. Tsigelny IF. Artificial intelligence in drug combination therapy. Brief Bioinform 2019;20:1434-48.
15. 15. Bess A, Berglind F, Mukhopadhyay S, , et al. Artificial intelligence for the discovery of novel antimicrobial agents for emerging infectious diseases. Drug Discov Today 2022;27:1099-107.
16. 16. Ong CWM, Blackbourn HD, Migliori GB. GPT-4, artificial intelligence and implications for publishing. Int J Tuberc Lung Dis 2023;27:425-26.
17. 17. Park Y, Casey D, Joshi I, et al. Emergence of New Disease: How Can Artificial Intelligence Help? Trends Mol Med 2020;26:627-9.
18. 18. Tran NK, Kretsch C, LaValley C, et al. Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients. Curr Opin Infect Dis 2023;36:235-42.
19. 19. Kulkarni S, Jha S. Artificial Intelligence, Radiology, and Tuberculosis: A Review. Acad Radiol 2020;27:71-5.
20. 20. Babcock S, Beverley J, Cowell LG, et al. The Infectious Disease Ontology in the age of COVID-19. J Biomed Semantics 2021;12:13. 21. Mali SN, Pratap AP. Targeting Infectious Coronavirus Disease 2019 (COVID-19) with Artificial Intelligence (AI) Applications: Evidence Based Opinion. Infect Disord Drug Targets 2021;21:475-7.
21. 22. Edeh MO, Dalal S, Dhaou IB, et al. Artificial Intelligence-Based Ensemble Learning Model for Prediction of Hepatitis C Disease. Front Public Health 2022;10:892371.
22. 23. Kaur I, Behl T, Aleya L, et al. Artificial intelligence as a fundamental tool in management of infectious diseases and its current implementation in COVID-19 pandemic. Environ Sci Pollut Res Int 2021;28:40515-32.
23. 24. Karimzadeh M, Ngo T, Lucas B, et al. Forecasting COVID-19 and Other Infectious Diseases for Proactive Policy: Artificial Intelligence Can Help. J Urban Health 2023;100:7-10.
24. 25. Kim J, Ahn I. Infectious disease outbreak prediction using media articles with machine learning models. Sci Rep 2021;11:4413.
25. 26. Castelvecchi D. Are ChatGPT and AlphaCode going to replace programmers? Nature 2022.
26. 27. Howard A, Hope W, Gerada A. ChatGPT and antimicrobial advice: the end of the consulting infection doctor? Lancet Infect Dis 2023;1473–3099:00113–5.
27. 28. Mehta P, Titanji BK. Baricitinib in COVID-19: a comingof-age from artifcial intelligence to reducing mortality. Lancet 2022;400:338–9.
28. 29. Wang SH. OpenAI - explain why some countries are excluded from ChatGPT. Nature 2023;615:34.
29. 30. Brainard J. Journals take up arms against AI-written text. Science 2023;379:740–1.
30. 31. He S, Leanse LG, Feng Y. Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases. Adv Drug Deliv Rev 2021;178:113922.
31. 32. Li C, Ye G, Jiang Y, et al. Artificial Intelligence in battling infectious diseases: A transformative role. J Med Virol 2024;96:e29355.
32. 33. Tran NK, Albahra S, Rashidi H, et al. Innovations in infectious disease testing: Leveraging COVID-19 pandemic technologies for the future. Clin Biochem 2023;117:10-5.
33. 34. Parvatikar PP, Patil S, Khaparkhuntikar K, et al. Artificial intelligence: Machine learning approach for screening large database and drug discovery. Antiviral Res 2023;220:105740.
34. 35. Giacobbe DR, Zhang Y, de la Fuente J. Explainable artificial intelligence and machine learning: novel approaches to face infectious diseases challenges. Ann Med 2023;55:2286336.
35. 36. Xiang Y, Du J, Fujimoto K, Li F, et al. Application of artificial intelligence and machine learning for HIV prevention interventions. Lancet HIV 2022;9:e54-e62.
36. 37. Malani P. Artificial Intelligence, Emerging Threats, and Diagnostic Advances-Highlights From ECCMID, Europe's Largest Infectious Disease Conference. JAMA 2023;329:1722-3.
37. 38. Equbal A, Masood S, Equbal I, et al. Artificial Intelligence against COVID-19 Pandemic: A Comprehensive Insight. Curr Med Imaging 2022;19:1-18.
38. 39. Barman RK, Mukhopadhyay A, Maulik U, et al. Identification of infectious disease-associated host genes using machine learning techniques. BMC Bioinformatics 2019;20:736.
39. 40. Kim K, Lee MK, Shin HK, et al. Development and application of survey-based artificial intelligence for clinical decision support in managing infectious diseases: A pilot study on a hospital in central Vietnam. Front Public Health 2022;10:1023098.
40. 41. Marcus JL, Sewell WC, Balzer LB, et al. Artificial Intelligence and Machine Learning for HIV Prevention: Emerging Approaches to Ending the Epidemic. Curr HIV/AIDS Rep 2020;17:171-9.
41. 42. Barbieri D, Giuliani E, Del Prete A, et al. How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic. Int J Environ Res Public Health 2021;18:7648.
42. 43. Garcia-Vidal C, Sanjuan G, Puerta-Alcalde P, et al. Artificial intelligence to support clinical decision-making processes. EBioMedicine 2019;46:27-9.