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Aims
Human-computer interactions (HCI) may have a relevant impact on the performance of Artificial Intelligence (AI). Studies show that although endoscopists assessing Barrett’s esophagus (BE) with AI improve their performance significantly, they do not achieve the level of the stand-alone performance of AI. One aspect of HCI is the impact of AI on the degree of certainty and confidence displayed by the endoscopist. Indirectly, diagnostic confidence when using AI may be linked to trust and acceptance of AI. In a BE video study, we aimed to understand the impact of AI on the diagnostic confidence of endoscopists and the possible correlation with diagnostic performance.
Methods
22 endoscopists from 12 centers with varying levels of BE experience reviewed ninety-six standardized endoscopy videos. Endoscopists were categorized into experts and non-experts and randomly assigned to assess the videos with and without AI. Participants were randomized in two arms: Arm A assessed videos first without AI and then with AI, while Arm B assessed videos in the opposite order. Evaluators were tasked with identifying BE-related neoplasia and rating their confidence with and without AI on a scale from 0 to 9.
Results
The utilization of AI in Arm A (without AI first, with AI second) significantly elevated confidence levels for experts and non-experts (7.1 to 8.0 and 6.1 to 6.6, respectively). Only non-experts benefitted from AI with a significant increase in accuracy (68.6% to 75.5%). Interestingly, while the confidence levels of experts without AI were higher than those of non-experts with AI, there was no significant difference in accuracy between these two groups (71.3% vs. 75.5%). In Arm B (with AI first, without AI second), experts and non-experts experienced a significant reduction in confidence (7.6 to 7.1 and 6.4 to 6.2, respectively), while maintaining consistent accuracy levels (71.8% to 71.8% and 67.5% to 67.1%, respectively).
Conclusions
AI significantly enhanced confidence levels for both expert and non-expert endoscopists. Endoscopists felt significantly more uncertain in their assessments without AI. Furthermore, experts with or without AI consistently displayed higher confidence levels than non-experts with AI, irrespective of comparable outcomes. These findings underscore the possible role of AI in improving diagnostic confidence during endoscopic assessment.
Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated. The measurements carried out over a wide spectral range, from visible light down to terahertz radiation. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.
OBJECTIVES
Due to severe limitations of dental pulp sensitivity tests, the direct recording of pulsed blood flow, using photoplethysmography (PPG), has been proposed. In vivo evaluation is methodologically difficult and in vitro models have hitherto been adversely influenced by shortcomings in emulating the in vivo situation. Consequently, the aim of this study was to test an improved data acquisition system and to use this configuration for recording pulsed blood in a new model.
MATERIALS AND METHODS
We introduced a PPG signal detection system by recording signals under different blood flow conditions at two wavelengths (625 and 940 nm). Pulsed blood flow signals were measured using an in vitro model, containing a molar with a glass pulp and a resin socket, which closely resembled in vivo conditions with regard to volumetric blood flow, pulp anatomy, and surrounding tissue.
RESULTS
The detection system showed improved signal strength without stronger blanketing of noise. On the tooth surface, it was possible to detect signals emanating from pulsed blood flow from the glass pulp and from surrounding tissue at 625 nm. At 940 nm, pulp derived signals were recorded, without interference signals from surrounding tissue.
CONCLUSION
The PPG-based method has the potential to detect pulsed blood flow in small volumes in the pulp and (at 625 nm) also in adjacent tissues.
CLINICAL RELEVANCE
The results show the need for clear differentiation of the spatial origins of blood flow signals of any vitality test method to be applied to teeth.
Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated over a wide spectral range, from visible to terahertz (THz) light. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.