1. Singhal K, Azizi S, Tu T, et al. Large language models encode clinical knowledge. Nature 2023; 620: 172-80.
2.
Esteva A, Robicquet A, Ramsundar B, et al. A guide to deep learning in healthcare. Nat Med 2019; 25: 24-9.
3.
Dave T, Athaluri SA, Singh S. ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations. Front Artif Intell 2023; 6: 1169595.
4.
Lewandowski M, Łukowicz P, Świetlik D, Barańska-Rybak W. An original study of ChatGPT-3.5 and ChatGPT-4 dermatological knowledge level based on the dermatology specialty certificate examinations. Clin Exp Dermatol 2024; 49: 686-91.
5.
Sallam M. ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. Healthcare 2023; 11: 887.
6.
Krajewski PK, Matusiak Ł, von Stebut E, et al. Quality-of-life impairment among patients with hidradenitis suppurativa: a cross-sectional study of 1795 patients. Life (Basel) 2021; 11: 34.
7.
Sabat R, Jemec GBE, Matusiak Ł, et al. Hidradenitis suppurativa. Nat Rev Dis Primers 2020; 6: 18.
8.
Lewandowski M, Świerczewska Z, Barańska-Rybak W. Hidradenitis suppurativa: a review of current treatment options. Int J Dermatol 2022; 61: 1152-64.
9.
Rymaszewska E, Karczewski M, Krajewski PK, et al. Patients’ expectations and satisfaction with the patient–doctor relationship in hidradenitis suppurativa. Healthcare 2023; 11: 3139.
10.
Heratizadeh A, Werfel T, Wollenberg A, et al. Effects of structured patient education in adults with atopic dermatitis: multicenter randomized controlled trial. J Allergy Clin Immunol 2017; 140: 845-53.e3.
11.
de Bes J, Legierse CM, Prinsen CAC, de Korte J. Patient education in chronic skin diseases: a systematic review. Acta Derm Venereol 2011; 91: 12-7.
12.
Bujnowska-Fedak MM, Waligóra J, Mastalerz-Migas A. The Internet as a source of health information and services. Adv Exp Med Biol 2019; 1211: 1-16.
13.
Hämeen-Anttila K, Pietilä K, Pylkkänen L, Pohjanoksa-Mäntylä M. Internet as a source of medicines information (MI) among frequent internet users. Res Social Adm Pharm 2018; 14: 758-64.
14.
Vance K, Howe W, Dellavalle RP. Social internet sites as a source of public health information. Dermatol Clin 2009; 27: 133-6.
15.
Revuz J. Hidradenitis suppurativa - patients’ frequently asked questions. Hidradenitis Suppurativa 2006; 187-92.
16.
Lee TC, Staller K, Botoman V, et al. ChatGPT answers common patient questions about colonoscopy. Gastroenterology 2023; 165: 509-11.e7.
17.
Moazzam Z, Cloyd J, Lima HA, Pawlik TM. Quality of ChatGPT responses to questions related to pancreatic cancer and its surgical care. Ann Surg Oncol 2023; 30: 6284-6.
18.
Samaan JS, Yeo YH, Rajeev N, et al. Assessing the accuracy of responses by the language model ChatGPT to questions regarding bariatric surgery. Obes Surg 2023; 33: 1790-6.
19.
Seth I, Cox A, Xie Y, et al. Evaluating chatbot efficacy for answering frequently asked questions in plastic surgery: a ChatGPT case study focused on breast augmentation. Aesthet Surg J 2023; 43: 1126-35.
20.
Cakir H, Caglar U, Yildiz O, et al. Evaluating the performance of ChatGPT in answering questions related to urolithiasis. Int Urol Nephrol 2024; 56: 17-21.
21.
Trager MH, Queen D, Bordone LA, et al. Assessing ChatGPT responses to common patient queries regarding basal cell carcinoma. Arch Dermatol Res 2023; 315: 2979-81.
22.
Ayers JW, Poliak A, Dredze M, et al. Comparing physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum. JAMA Intern Med 2023; 183: 589-96.
23.
Mondal H, Dash I, Mondal S, Behera JK. ChatGPT in answering queries related to lifestyle-related diseases and disorders. Cureus 2023; 15: e48296.
24.
Walker HL, Ghani S, Kuemmerli C, et al. Reliability of medical information provided by ChatGPT: assessment against clinical guidelines and patient information quality instrument. J Med Internet Res 2023; 25: e47479.
25.
Verweel L, Newman A, Michaelchuk W, et al. The effect of digital interventions on related health literacy and skills for individuals living with chronic diseases: a systematic review and meta-analysis. Int J Med Inform 2023; 177: 105114.
26.
Prussick L, Tonelli S, Gottlieb AB, et al. Improving health literacy and treatment understanding of hidradenitis suppurativa using group educational interventions. J Dermatolog Treat 2019; 30: 708-13.
27.
Ayre J, Mac O, McCaffery K, et al. New frontiers in health literacy: using ChatGPT to simplify health information for people in the community. J Gen Intern Med 2024; 39: 573-7.
28.
Health Promotion Glossary of Terms 2021 [WWW Document]. URL https://www.who.int/publications/i/item/9789240038349 [accessed on 17 December 2023].
29.
Staab D, Diepgen TL, Fartasch M, et al. Age related, structured educational programmes for the management of atopic dermatitis in children and adolescents: multicentre, randomised controlled trial. BMJ 2006; 332: 933.
30.
Miller TA. Health literacy and adherence to medical treatment in chronic and acute illness: a meta-analysis. Patient Educ Couns 2016; 99: 1079-86.
31.
Wang X, Sanders HM, Liu Y, et al. ChatGPT: promise and challenges for deployment in low- and middle-income countries. Lancet Reg Health West Pac 2023; 41: 100905.
32.
Guo J, Li B. The application of medical artificial intelligence technology in rural areas of developing countries. Health Equity 2018; 2: 174.
33.
Nazir S, Dickson DM, Akram MU. Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks. Comput Biol Med 2023; 156: 106668.
34.
Ray PP. Refining the application of artificial intelligence in the water domain: Exploring the potential of ChatGPT. Sci Total Environ 2023; 892: 164638.