The COSMIN community updated the COSMIN-RoB checklist on reliability and measurement error in 2021. The updated checklist can be applied to the assessment of all types of outcome measurement studies, including clinician-reported outcome measures (ClinPOMs), performance-basd outcome measurement instruments (PerFOMs), and laboratory values. In order to help readers better understand and apply the updated COSMIN-RoB checklist and provide methodological references for conducting systematic reviews of ClinPOMs, PerFOMs and laboratory values, this paper aimed to interpret the updated COSMIN-RoB checklist on reliability and measurement error studies.
Cervical intraepithelial neoplasia is the primary type of cervical precancerous lesion; however, manual clinical diagnosis is prone to bias and has limited grading accuracy. To achieve precise automated grading of CIN, this paper proposes a multimodal fusion Swin Transformer model and develops a corresponding computer-aided diagnosis system. This method employs three-channel fusion of raw images, cervical mask images, and directional gradient histogram features to enhance lesion texture and location information. Within the Swin Transformer backbone, an atrous spatial pyramid pooling module channel attention module and a convolutional feature extraction module are embedded to balance global semantic and local detail features. A focal loss function is adopted to address class imbalance in the dataset and improve the model’s ability to identify difficult-to-classify samples. On a dataset of 3 915 clinical colposcopy images, the model achieved an overall accuracy of 90.01%, precision of 87.55%, recall of 86.17%, F1 score of 89.13%, outperforming baseline models such as VGG, ResNet, and Swin Transformer. The developed system integrates image quality screening, lesion identification, and three-level classification functions, providing an effective tool for the rapid and objective screening of clinical cervical precancerous lesions.
ObjectiveTo construct a framework and functional items of a scientific research assistant tool for conducting systematic review for patient-reported outcome measures. MethodsBased on the research foundation and work experience of the system evaluation of two patient-reported outcome measures systematic reviews carried out by the research group in the early stage, the framework and function system of scientific research aid tool was initially constructed, and two rounds of correspondence were carried out by Dephi expert consultation method. ResultsThe effective recovery rates of the two rounds of expert consultation questionnaires were 90% and 100%, the expert authority coefficient was 0.839, and the compatibility coefficients of suitability and importance were 0.105 and 0.177, respectively. The final the patient-reported outcome measures tool system evaluation scientific research aid tool system consists of 7 frames and 31 items. ConclusionThis study has developed a scientific and comprehensive set of functional criteria for research-assistant tools that systematically review patient-reported outcome measures based on the COSMIN methodology and it lays the foundation for subsequent tool research and development.