Page 108 - DP-2-1
P. 108

Design+                                                                   AI’s role in medical history taking



            Availability of data                                  Today and tomorrow. Front Med (Lausanne). 2020;7:27.

            The interview transcripts are available on request from the      doi: 10.3389/fmed.2020.00027
            authors.                                           11.  Sun Y. Modelling methods of artificial intelligence in
                                                                  medical application. Appl Comput Eng. 2023;18:42-47.
            References
                                                                  doi: 10.54254/2755-2721/18/20230962
            1.   Baier J, Kovács-Ondrejkovic O, Zimmermann T,  et al.
               Changing  Work  Preferences  in  the  Age  of  GenAI:  Decoding   12.  Zhu J, Valmianski I, Kannan A. Dialogue-contextualized
               Global  Talent; 2024. Available online: https://www.bcg.  re-ranking for medical history-taking. Proc Mach Learn Res.
               com/publications/2024/how-work-preferences-are-    2023;219:1-17.
               shifting-in-the-age-of-genai?utm_campaign=digital-  13.  Maicher KR, Stiff A, Scholl M, et al. Artificial intelligence in
               t ransfor mat ion&ut m_content=202406&ut m_        virtual standardized patients: Combining natural language
               des cr i p t io n=le ader s hi p_b y_desig n&u t m_  understanding and rule based dialogue management to
               geo=global&utm_medium=email&utm_source=esp&utm_    improve conversational fidelity. Med Teach. 2022; 8:1-7.
               t opic=p e op le_on_a i&ut m_u s er t o k en=CRM_
               cc19cfbd1c3fb5ee91ce7f5a0f0c073d5e53d4a9&mkt_      doi: 10.1080/0142159X.2022.2130216.
               tok=nzk5lulpqi04odmaaagt-n0gxfowmluduzuippwsgc0e_1e4  14.  Hong G, Smith M, Lin S. The AI will see you now: Feasibility
               ffu0clhb4rjo6kunnqhit8nr3lyjs1iqgrqgvti0h2bvsnn6yltbqio8r  and acceptability of a conversational AI medical interviewing
               a5k60lmmexjdvw5g9paar-U [Last accessed on 2025 Mar 08].  system. JMIR Form Res. 2022;6:e37028.
            2.   Golhar SP, Kekapure SS. Artificial intelligence in healthcare-a      doi: 10.2196/37028
               review. Int J Sci Res Sci Technol. 2022;9:381-387.
                                                               15.  IEEE.  2023  27   International Conference Information
                                                                               th
               doi: 10.32628/IJSRST229454                         Visualisation (IV). Tampere, Finland: IEEE; 2023.
            3.   Morrow E, Zidaru T, Ross F,  et al. Artificial intelligence   16.  Karpov OE, Pitsik EN, Kurkin SA,  et al. Analysis of
               technologies and compassion in healthcare: A  systematic   publication activity and research trends in the field of AI
               scoping review. Front Psychol. 2022;13:971044.     medical applications: Network approach. Int J Environ Res
               doi: 10.3389/fpsyg.2022.971044                     Public Health. 2023;20:5335.
            4.   Singhal M, Gupta L, Hirani K. A  comprehensive analysis      doi: 10.3390/ijerph20075335
               and review of artificial intelligence in anaesthesia. Cureus.   17.  Cheng ECK, Wang T, Schlippe T, Beligiannis GN, editors.
               2023;15:e45038.                                    Artificial Intelligence in Education Technologies: New
               doi: 10.7759/cureus.45038                          Development and Innovative Practices. Singapore: Springer
                                                                  Nature Singapore; 2023.
            5.   Hashimoto DA, Witkowski E, Gao L, Meireles O, Rosman G.
               Artificial intelligence in anesthesiology: Current techniques,   18.  Yokoi R, Eguchi Y, Fujita T, Nakayachi K. Artificial
               clinical applications, and limitations.  Anesthesiology.   intelligence is trusted less than a doctor in medical treatment
               2020;132:379-394.                                  decisions: Influence of perceived care and value similarity.
               doi: 10.1097/ALN.0000000000002960.                 Int J Hum Comput Interact. 2021;37:981-990.
            6.   Zhou XY, Guo Y, Shen M, Yang GZ. Application of artificial      doi: 10.1080/10447318.2020.1861763
               intelligence in surgery. Front Med. 2020;14:417-430.  19.  Grüne S. Medical history and physical examination. German
               doi: 10.1007/s11684-020-0770-0.                    Med Weeklies. 2016;141:24-27.
            7.   Navarrete-Welton AJ, Hashimoto DA. Current applications      doi: 10.1055/s-0041-106337
               of artificial intelligence for intraoperative decision support   20.  Zuin M, Rigatelli G, Zuliani G, Faggian G, Roncon L. The
               in surgery. Front Med. 2020;14:369-381.            secret of the questions: Medical interview in 21   century.
                                                                                                      st
               doi: 10.1007/s11684-020-0784-7.                    Eur J Intern Med. 2016;35:e21-e22.
            8.   Shalev-Shwartz S, Ben-David S.  Understanding  Machine      doi: 10.1016/j.ejim.2016.06.032.
               Learning: From Theory to Algorithms. Cambridge:   21.  Westrin CG. The reliability of auto-anamnesis. A study of
               Cambridge University Press; 2022.                  statements regarding low back trouble.  Scand J Soc Med.
            9.   Segato A, Marzullo A, Calimeri F, Momi E. Artificial   1974;2:23-35.
               intelligence for brain diseases: A  systematic review.  APL      doi: 10.1177/140349487400200104
               Bioeng. 2020;4:041503.
                                                               22.  Yang YC, Islam SU, Noor A, Khan S, Afsar W, Nazir S.
               doi: 10.1063/5.0011697
                                                                  Influential usage of big data and artificial intelligence in
            10.  Briganti G, Le Moine O. Artificial intelligence in medicine:   healthcare. Comput Math Methods Med. 2021;2021:5812499.


            Volume 2 Issue 1 (2025)                         11                               doi: 10.36922/dp.7675
   103   104   105   106   107   108   109   110   111   112   113