A content-aware chatbot based on GPT 4 provides trustworthy recommendations for Cone-Beam CT guidelines in dental imaging

被引:4
|
作者
Russe, Maximilian Frederik [1 ]
Rau, Alexander [1 ,2 ]
Ermer, Michael Andreas [3 ]
Rothweiler, Rene [3 ]
Wenger, Sina [3 ]
Kloeble, Klara [3 ]
Schulze, Ralf K. W. [4 ]
Bamberg, Fabian [1 ]
Schmelzeisen, Rainer [3 ]
Reisert, Marco [5 ,6 ]
Semper-Hogg, Wiebke [3 ]
机构
[1] Univ Freiburg, Fac Med, Med Ctr, Dept Diagnost & Intervent Radiol, D-79106 Freiburg, Germany
[2] Univ Freiburg, Fac Med, Med Ctr, Dept Neuroradiol, D-79106 Freiburg, Germany
[3] Univ Freiburg, Fac Med, Med Ctr, Dept Oral & Maxillofacial Surg, Breisacher Str 64, D-79106 Freiburg, Germany
[4] Univ Bern, Sch Dent Med, Dept Oral Surg & Stomatol & Oral Diagnost, Div Oral Diagnost Sci, CH-3010 Bern, Switzerland
[5] Univ Freiburg, Dept Diagnost & Intervent Radiol, Div Med Phys, Med Ctr,Fac Med, D-79106 Freiburg, Germany
[6] Univ Freiburg, Fac Med, Med Ctr, Dept Stereotact & Funct Neurosurg, D-79106 Freiburg, Germany
关键词
Cone-Beam CT; dental imaging; natural language processing; chatbot;
D O I
10.1093/dmfr/twad015
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Objectives To develop a content-aware chatbot based on GPT-3.5-Turbo and GPT-4 with specialized knowledge on the German S2 Cone-Beam CT (CBCT) dental imaging guideline and to compare the performance against humans.Methods The LlamaIndex software library was used to integrate the guideline context into the chatbots. Based on the CBCT S2 guideline, 40 questions were posed to content-aware chatbots and early career and senior practitioners with different levels of experience served as reference. The chatbots' performance was compared in terms of recommendation accuracy and explanation quality. Chi-square test and one-tailed Wilcoxon signed rank test evaluated accuracy and explanation quality, respectively.Results The GPT-4 based chatbot provided 100% correct recommendations and superior explanation quality compared to the one based on GPT3.5-Turbo (87.5% vs. 57.5% for GPT-3.5-Turbo; P = .003). Moreover, it outperformed early career practitioners in correct answers (P = .002 and P = .032) and earned higher trust than the chatbot using GPT-3.5-Turbo (P = 0.006).Conclusions A content-aware chatbot using GPT-4 reliably provided recommendations according to current consensus guidelines. The responses were deemed trustworthy and transparent, and therefore facilitate the integration of artificial intelligence into clinical decision-making.
引用
收藏
页码:109 / 114
页数:6
相关论文
共 50 条
  • [31] A cone-beam CT based technique to augment the 3D virtual skull model with a detailed dental surface
    Swennen, G. R. J.
    Mommaerts, M. Y.
    Abeloos, J.
    De Clercq, C.
    Lamoral, P.
    Neyt, N.
    Casselman, J.
    Schutyser, F.
    INTERNATIONAL JOURNAL OF ORAL AND MAXILLOFACIAL SURGERY, 2009, 38 (01) : 48 - 57
  • [32] Imaging Study of Pseudo-CT Synthesized From Cone-Beam CT Based on 3D CycleGAN in Radiotherapy
    Sun, Hongfei
    Fan, Rongbo
    Li, Chunying
    Lu, Zhengda
    Xie, Kai
    Ni, Xinye
    Yang, Jianhua
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [33] Dose Estimation by Geant4-Based Simulations for Cone-Beam CT Applications: A Systematic Review
    Cabanas, Ana M.
    Arriagada-Benitez, Mauricio
    Ubeda, Carlos
    Meseguer-Ruiz, Oliver
    Arce, Pedro
    APPLIED SCIENCES-BASEL, 2021, 11 (13):
  • [34] Modeling and design of a cone-beam CT head scanner using task-based imaging performance optimization
    Xu, J.
    Sisniega, A.
    Zbijewski, W.
    Dang, H.
    Stayman, J. W.
    Wang, X.
    Foos, D. H.
    Aygun, N.
    Koliatsos, V. E.
    Siewerdsen, J. H.
    PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (08): : 3180 - 3207
  • [35] A knowledge-based cone-beam x-ray CT algorithm for dynamic volumetric cardiac imaging
    Wang, G
    Zhao, SY
    Heuscher, D
    MEDICAL PHYSICS, 2002, 29 (08) : 1807 - 1822
  • [36] Image noise due to quantum fluctuations in flat-panel detector based cone-beam CT imaging
    Zhang, Y
    Ning, R
    Conover, D
    Yu, Y
    Medical Imaging 2005: Physics of Medical Imaging, Pts 1 and 2, 2005, 5745 : 656 - 663
  • [37] 4D Respiratory Cone-Beam CT Imaging for Thoracic Interventions on Robotic C-Arm Systems
    Reynolds, T.
    Dillon, O. T.
    Hindley, N.
    Ma, Y.
    Stayman, J. W.
    Bazalova-Carter, M.
    MEDICAL PHYSICS, 2024, 51 (09) : 6643 - 6643
  • [38] 3D and 4D imaging from multi-threaded cone-beam CT scans
    Knaup, Michael
    Kachelriess, Marc
    Kalender, Willi A.
    2005 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOLS 1-5, 2005, : 1881 - 1885
  • [39] 4D Cone-Beam CT Ventilation Imaging to Facilitate Adaptive Functional Avoidance Lung Cancer Radiotherapy
    Kipritidis, J.
    Eslick, E.
    Cooper, B.
    O'Brien, R.
    Yamamoto, T.
    Williamson, J. F.
    Keall, P.
    JOURNAL OF THORACIC ONCOLOGY, 2012, 7 (09) : S323 - S323
  • [40] GPU-Based 4D Cone-Beam CT Reconstruction Using Adaptive Meshing Method
    Zhong, Z.
    Gu, X.
    Iyengar, P.
    Mao, W.
    Guo, X.
    Wang, J.
    MEDICAL PHYSICS, 2015, 42 (06) : 3219 - 3219