Oblique lumbar interbody fusion (OLIF) has been driven to the maturity stage in recent years. However, postoperative symptoms such as thigh paresthesia resulting from intraoperative retraction of the psoas major (PM) have sometimes occurred. The aim of this study was to assess the different positions and morphology of PM muscles and their relationship with clinical outcomes after OLIF by introducing the Moro zones. Patients who underwent L4-5 OLIF at our institution between April 2019 and June 2021 were reviewed and all data were recorded. All patients were grouped by Moro zones into a Moro A cohort and a Moro I and II cohort based on the front edges of their left PM muscles. A total of 94 patients were recruited, including 57 in the Moro A group and 37 in the Moro I and II group. Postoperative thigh pain or numbness occurred in 12 (21.1%) and 2 (5.4%) patients in the Moro A group and the Moro I and II group, respectively. There was no difference in the psoas major transverse diameter (PMTD) between groups preoperatively, while longer PMTD was revealed postoperatively in the Moro A group. The operating window (OW) and psoas major sagittal diameter (PMSD) showed significant differences within and between groups. Thirteen patients had teardrop-shaped PM muscles, with 92.3% in the Moro A group showing significantly worse clinical scores at 1-week follow-up. The Moro zones of the PM affected the short-term outcomes after OLIF. Preoperative measurements and analysis of OW, PMSD and PM morphology should be performed as necessary to predict short-term outcomes.

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Deep learning evaluation is a new direction formed by the intersection of multiple domains, and the core issue is how to visualize collaborative learning models to motivate learners. Therefore, this paper realizes real-time knowledge sharing and facilitates learners' interaction through computer-supported collaborative learning (CSCL) technology. In this paper, we collect, label, and analyze data based on five modalities: brain, behavior, cognition, environment, and technology. In this paper, a computer-supported collaborative learning process analysis model is developed under the threshold of multimodal data analysis. The model is based on roles and CSCL for intelligent network collaboration. This paper designs and develops an interactive visualization tool to support online collaborative learning process analysis. In addition, this paper conducts a practical study in an online classroom. The results show that the model and the tool can be effectively used for online collaborative learning process analysis, and the test model results fit well. The entropy index of the test model took a value of about 0.85, and about less than 10% of the individuals were assigned to the wrong profile. During the test, the participation of participants gradually increased from 5% to about 25%, and the participation effect improved by about 80%. This indicates the strong applicability value of the computer-supported collaborative learning process analysis model under the multimodal data analysis perspective.

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