Kurian N, Cherian JM, Sudharson NA, Varghese KG, Wadhwa S. AI is now everywhere. Br Dent J. 2023;234:72–72.

Article  CAS  PubMed  Google Scholar 

U D, Z D, W HJ. ChatGPT-A promising generative AI tool and its implications for cancer care. Cancer [Internet]. 2023;129. Available from: http://pubmed.ncbi.nlm.nih.gov/37183438/. Accessed 25 Feb 2024.

Johnson SB, King AJ, Warner EL, Aneja S, Kann BH, Bylund CL. Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information. JNCI Cancer Spectr [Internet]. 2023;7. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10020140/. Accessed 26 Sept 2023.

Zhu L, Mou W, Chen R. Can the ChatGPT and other large language models with internet-connected database solve the questions and concerns of patient with prostate cancer and help democratize medical knowledge? J Transl Med. 2023;21:1–4.

Article  Google Scholar 

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49.

Article  PubMed  Google Scholar 

Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence - ScienceDirect [Internet]. 2018. Available from: https://web.archive.org/web/20181121191205/https://www.sciencedirect.com/science/article/pii/S0007681318301393. Accessed 24 Sept 2023.

Ramesh AN, Kambhampati C, Monson JRT, Drew PJ. Artificial intelligence in medicine. Ann R Coll Surg Engl. 2004;86:334–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

What is artificial intelligence? [Internet]. 2015. Available from: https://web.archive.org/web/20151118212402/http://www-formal.stanford.edu/jmc/whatisai/whatisai.html. Accessed 24 Sept 2023.

Zhang C, Lu Y. Study on artificial intelligence: The state of the art and future prospects. J Ind Inf Integr. 2021;23:100224.

Google Scholar 

Shortliffe EH, Davis R, Axline SG, Buchanan BG, Green CC, Cohen SN. Computer-based consultations in clinical therapeutics: Explanation and rule acquisition capabilities of the MYCIN system. Comput Biomed Res. 1975;8:303–20.

Article  CAS  PubMed  Google Scholar 

Buchanan B, Shortliffe E. Rule-based Expert System – The MYCIN Experiments of the Stanford Heuristic Programming Project. SERBIULA Sist. Libr. 20. 1984. https://doi.org/10.1016/0004-3702(85)90067-0.

Rayhan S, Gross D. Revolutionizing intelligence: Unraveling the frontiers of advanced artificial intelligence and its impact on society. 2023. https://doi.org/10.13140/RG.2.2.18500.60808.

Averkin AN, Yarushev SA. Evolution of artificial neural networks. 2018. Available from: https://libeldoc.bsuir.by/handle/123456789/30338. Accessed 26 Mar 2024.

Uddin S, Khan A, Hossain ME, Moni MA. Comparing different supervised machine learning algorithms for disease prediction. BMC Med Inform Decis Mak. 2019;19:281.

Article  PubMed  PubMed Central  Google Scholar 

Kavakiotis I, Tsave O, Salifoglou A, Maglaveras N, Vlahavas I, Chouvarda I. Machine learning and data mining methods in diabetes research. Comput Struct Biotechnol J. 2017;15:104–16.

Article  PubMed  PubMed Central  Google Scholar 

Sharma S, Aggarwal A, Choudhury T. Breast cancer detection using machine learning algorithms. 2018 Int Conf Comput Tech Electron Mech Syst CTEMS [Internet]. 2018 . pp. 114–8. Available from: https://ieeexplore.ieee.org/abstract/document/8769187. Accessed 26 Sept 2023.

LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436–44.

Article  CAS  PubMed  Google Scholar 

Nadkarni PM, Ohno-Machado L, Chapman WW. Natural language processing: an introduction. J Am Med Inform Assoc. 2011;18:544–51.

Article  PubMed  PubMed Central  Google Scholar 

Kreimeyer K, Foster M, Pandey A, Arya N, Halford G, Jones SF, et al. Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review. J Biomed Inform. 2017;73:14–29.

Article  PubMed  PubMed Central  Google Scholar 

Sheikhalishahi S, Miotto R, Dudley JT, Lavelli A, Rinaldi F, Osmani V. Natural language processing of clinical notes on chronic diseases: systematic review. JMIR Med Inform. 2019;7:e12239.

Article  PubMed  PubMed Central  Google Scholar 

Yang X, Mu D, Peng H, Li H, Wang Y, Wang P, et al. Research and application of artificial intelligence based on electronic health records of patients with cancer: systematic review. JMIR Med Inform. 2022;10:e33799.

Article  PubMed  PubMed Central  Google Scholar 

G E. The Role of ChatGPT, Generative language models, and artificial intelligence in medical education: A conversation with ChatGPT and a call for papers. JMIR Med Educ [Internet]. 2023;9. Available from: http://pubmed.ncbi.nlm.nih.gov/36863937/. Accessed 4 Oct 2023.

Lee P, Bubeck S, Petro J. Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine. N Engl J Med. 2023;388:1233–9.

Article  PubMed  Google Scholar 

Keifenheim KE, Teufel M, Ip J, Speiser N, Leehr EJ, Zipfel S, et al. Teaching history taking to medical students: a systematic review. BMC Med Educ. 2015;15:1–12.

Article  Google Scholar 

Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat Rev Clin Oncol. 2018;15:81–94.

Article  CAS  PubMed  Google Scholar 

Blum J, et al. Pearls and pitfalls of ChatGPT in medical oncology. Trends Cancer. 2023;9:788–90.

Article  PubMed  Google Scholar 

Campanella P, Lovato E, Marone C, Fallacara L, Mancuso A, Ricciardi W, et al. The impact of electronic health records on healthcare quality: a systematic review and meta-analysis. Eur J Public Health. 2016;26:60–4.

Article  PubMed  Google Scholar 

Huang H, Zheng O, Wang D, Yin J, Wang Z, Ding S, et al. ChatGPT for shaping the future of dentistry: the potential of multi-modal large language model. Int J Oral Sci. 2023;15:1–13.

Article  PubMed  PubMed Central  Google Scholar 

Borrell-Carrió F, Suchman AL, Epstein RM. The biopsychosocial model 25 years later: principles, practice, and scientific inquiry. Ann Fam Med. 2004;2:576.

Article  PubMed  PubMed Central  Google Scholar 

I D, F F-R, S H, Aa L, Jm G, Ms F, et al. ChatGPT is not ready yet for use in providing mental health assessment and interventions. Front Psychiatry [Internet]. 2024;14. Available from: http://pubmed.ncbi.nlm-nih.gov/38239905/. Accessed 23 Jan 2024.

Elyoseph Z, Hadar-Shoval D, Asraf K, Lvovsky M. ChatGPT outperforms humans in emotional awareness evaluations. Front Psychol [Internet]. 2023;14. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10254409/. Accessed 28 Sept 2023.

Bhayana R, Krishna S, Bleakney RR. Performance of ChatGPT on a radiology board-style examination: insights into current strengths and limitations. Radiology. 2023;307:e230582.

Article  PubMed  Google Scholar 

Fink MA, Bischoff A, Fink CA, Moll M, Kroschke J, Dulz L, et al. Potential of ChatGPT and GPT-4 for data mining of free-text CT reports on lung cancer. Radiology. 2023;308:e231362.

Article  PubMed  Google Scholar 

Z S, M AW, L N, N N, R S, H F, et al. Evaluation of GPT-4’s chest x-ray impression generation: A reader study on performance and perception. J Med Internet Res [Internet]. 2023;25. Available from: http://pubmed.ncbi.nlm.nih-gov/38133918/. Accessed 23 Jan  2024.

C EM, Z SC, N AT, A KM, S HM, K M. Feasibility and acceptability of ChatGPT generated radiology report summaries for cancer patients. Digit Health [Internet]. 2023;9. Available from: http://pubmed.ncbi.nlm.nih.gov/38130802/. Accessed 23 Jan 2024.

Haver HL, Ambinder EB, Bahl M, Oluyemi ET, Jeudy J, Yi PH. Appropriateness of breast cancer prevention and screening recommendations provided by ChatGPT. Radiology. 2023;307:e230424.

Article  PubMed  Google Scholar 

Martin-Carreras T, Cook TS, Kahn CE Jr. Readability of radiology reports: implications for patient-centered care. Clin Imaging. 2019;54:116–20.

Article  PubMed  Google Scholar 

Lyu Q, Tan J, Zapadka ME, Ponnatapura J, Niu C, Myers KJ, et al. Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: results, limitations, and potential. Vis Comput Ind Biomed Art [Internet]. 2023;6. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10192466/. Accessed 4 Oct 2023.

New horizons: the potential role of OpenAI’s ChatGPT in clinical radiology. J Am Coll Radiol [Internet]. 2023. Available from: http://www.sciencedirect.com/science/article/pii/S1546144023005367 . Accessed 4 Oct 2023.

J K, S B, D J, M A, S AT, T J, et al. ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports. Eur Radiol [Internet]. 2023. Available from: http://pubmed.ncbi.nlm.nih.gov/37794249/. Accessed 23 Jan 2024.

T WCC, N SN, C HY, N HHM, W D, W YTF, et al. Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy. Cancer Commun Lond Engl [Internet]. 2020;40. Available from: http://pubmed.ncbi.nlm.nih.gov/32301585/. Accessed 10 Oct 2023.

O ET, A EB, S O, W MJ, Y PH, M KS. Appropriateness of information provided by ChatGPT regarding breast pathologic diagnoses. AJR Am J Roentgenol [Internet]. 2024. Available from: http://pubmed.ncbi.nlm.nih.gov/38170831/. Accessed 23 Jan  2024.

Wang AY, Lin S, Tran C, Homer RJ, Wilsdon D, Walsh JC, et al. Assessment of pathology domain-specific knowledge of ChatGPT and comparison to human performance. Arch Pathol Lab Med [Internet]. 2024. Available from: https://doi.org/10.5858/arpa.2023-0296-OA. Accessed 23 Jan 2024.

Cui C, Shu W, Li P. Fluorescence in situ hybridization: cell-based genetic diagnostic and research applications. Front Cell Dev Biol. 2016;4:207976.

Article  Google Scholar 

Ellison G, Zhu G, Moulis A, Dearden S, Speake G, McCormack R. EGFR mutation testing in lung cancer: a review of available methods and their use for analysis of tumour tissue and cytology samples. J Clin Pathol. 2013;66:79–89.

Article  CAS  PubMed  Google Scholar 

Lindeman, Neal I et al. Updated molecular testing guideline for the selection of lung cancer patients for treatment with targeted tyrosine kinase inhibitors: guideline from the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology. J Thorac Oncol. 2018;13:323–58.

Zhang N-N, Liu Y-T, Ma L, Wang L, Hao X-Z, Yuan Z, et al. The molecular detection and clinical significance of ALK rearrangement in selected advanced non-small cell lung cancer: ALK expression provides insights into ALK targeted therapy. PLoS ONE. 2014;9:e84501.

Article  PubMed  PubMed Central  Google Scholar 

S AT, B TM, de M F, F E, G Y, L G, et al. First-Line lorlatinib or crizotinib in advanced ALK-positive lung cancer. N Engl J Med [Internet]. 2020;383. Available from: