Objective: Auditory brainstem responses (ABR) evoked by tone burst is an important method of hearing assessment in referral infants after hearing screening. The present study was to compare the thresholds of tone burst ABR with filter settings of 30 - 1500 Hz and 30 - 3000 Hz at each frequency, figure out the characteristics of ABR thresholds with the two filter settings and the effect of the waveform judgement, so as to select a more optimal frequency specific ABR test parameter.
Methods: Thresholds with filter settings of 30 - 1500 Hz and 30 - 3000 Hz in children aged 2 - 33 months were recorded by click, tone burst ABR. A total of 18 patients (8 male/10 female), 22 ears were included.
Results: The thresholds of tone burst ABR with filter settings of 30 - 3000 Hz were higher than that with filter settings of 30 - 1500 Hz. Significant difference was detected for that at 0.5 kHz and 2.0 kHz (t values were 2.238 and 2.217, P < 0.05), no significant difference between the two filter settings was detected at the rest frequencies tone evoked ABR thresholds. The waveform of ABR with filter settings of 30 - 1500 Hz was smoother than that with filter settings of 30 - 3000 Hz at the same stimulus intensity. Response curve of the latter appeared jagged small interfering wave.
Conclusions: The filter setting of 30 - 1500 Hz may be a more optimal parameter of frequency specific ABR to improve the accuracy of frequency specificity ABR for infants' hearing assessment.
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Ensuring trustworthiness is fundamental to the development of artificial intelligence (AI) that is considered societally responsible, particularly in cancer diagnostics, where a misdiagnosis can have dire consequences. Current digital pathology AI models lack systematic solutions to address trustworthiness concerns arising from model limitations and data discrepancies between model deployment and development environments. To address this issue, we developed TRUECAM, a framework designed to ensure both data and model trustworthiness in non-small cell lung cancer subtyping with whole-slide images.
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Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan; Institute of NanoEngineering and Microsystems, National Tsing Hua University, Hsinchu, Taiwan. Electronic address:
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