Objective To investigate the application effect of a virtual simulation teaching system based on DeepSeek technology in the clinical training of neonatal resuscitation. Methods A total of 48 clinical medicine (“5+3” integrated program) students from the 2020 cohort, interning in the Department of Neonatology of the First Affiliated Hospital of Harbin Medical University between January and June 2025, were selected and randomly divided into a trial group (n=24) and a control group (n=24). The trial group received training using a virtual simulation teaching system integrated with DeepSeek technology, featuring dynamic physiological response, natural language interaction, and hierarchical intelligent feedback. The control group received traditional virtual simulation teaching. After 6 hours of teaching, outcomes were evaluated through theoretical assessments, objective structured clinical examination (OSCE), key decision-making accuracy, and teaching satisfaction questionnaires. Results The theoretical score (93.5±3.3 vs. 84.7±4.9), OSCE score (95.3±2.6 vs. 86.1±4.3), and key decision-making accuracy [(91.6±3.7)% vs. (77.3±6.4)%] of the trial group were significantly higher than those of the control group (P<0.001). The trial group outperformed the control group in all OSCE subdomain scores (rapid assessment and initial resuscitation: 24.1±1.0 vs. 21.3±2.2; positive pressure ventilation: 23.8±1.2 vs. 20.1±2.1; chest compressions: 18.9±1.1 vs. 16.2±1.8; drug therapy: 14.3±0.9 vs. 12.0±1.5; teamwork and communication: 14.2±0.8 vs. 11.5±1.6) and in the accuracy rates for all key decision points [whether to initiate initial resuscitation: (93.8±4.5)% vs. (82.1±8.7)%; whether to initiate positive pressure ventilation: (92.9±5.3)% vs. (79.6±10.2)%; whether to correct ventilation: (90.4±6.1)% vs. (75.0±11.5)%; whether to initiate chest compressions (94.2±5.1)% vs. (70.8±12.3)%; whether to use epinephrine: (92.5±6.2)% vs. (68.3±14.1)%], with all differences being statistically significant (P<0.001). The teaching satisfaction survey showed that the satisfaction rates in the trial group for the dimensions of immersion (95.8% vs. 54.2%), knowledge understanding (91.7% vs. 58.3%), skill improvement (91.7% vs. 62.5%), decision-making logic (95.8% vs. 50.0%), feedback effectiveness (95.8% vs. 41.7%), and learning confidence (91.7% vs. 45.8%) were all significantly higher than those in the control group (P<0.05). Conclusion The DeepSeek-based virtual simulation teaching system can effectively enhance the quality of neonatal resuscitation training, significantly improving students’ clinical decision-making abilities, operational skills, and teamwork competence, demonstrating good application prospects in medical education.
ObjectiveTo investigate the short-term effectiveness of three-dimensional (3D) printing personalized prosthesis in the treatment of giant cell tumor of bone around knee joint.MethodsA clinical data of 9 patients with giant cell tumor of bone around knee joints and met the inclusive criteria between May 2014 and August 2017 was retrospectively analysed. There were 4 males and 5 females, with an average age of 35.8 years (range, 24-50 years). The lesion located at the distal femur in 4 cases and at the proximal tibia in 5 cases. The disease duration was 5-25 months (mean, 12.9 months). According to Campanacci grading, there were 2 patients of grade Ⅰ and 7 of grade Ⅱ. The 3D printing personalized prosthesis was designed based on the CT scanning and 3D reconstruction prepared before operation. All patients were treated with the tumor resection and 3D printing personalized prosthesis reconstruction. The radiological examination was taken to observe the tumor recurrence and the Musculoskeletal Tumor Society 1993 (MSTS93) score was used to evaluate the knee function.ResultsAll operations were successful and all incisions healed by first intention without early complications. All patients were followed up 24-40 months (mean, 31.2 months). At last follow-up, no complication such as pain, pathological fracture, prosthesis loosening, or tumor recurrence occurred. The MSTS93 score was 20-29 (mean, 24.7). The knee function was rated as excellent in 6 cases and good in 3 cases, with the excellent and good rate of 100%. ConclusionFor giant cell tumor of bone around knee joint, 3D printing personalized prosthesis has the advantages of bio-fusion with host bone, mechanical stability, good joint function, and ideal short-term effectiveness. But the middle- and long-term effectiveness still need to be further observed.
This paper aims to explore the feasibility of building a finite element model of left atrial diverticulum (LAD) using reverse engineering software based on computed tomography (CT) images. The study was based on a three-dimensional cardiac CT images of a atrial fibrillation patient with LAD. The left atrium and LAD anatomical features were accurately reproduced by using Geomagic Studio 12 and Mimics 15 reverse engineering software. In addition, one left atrial model with LAD and one without LAD were created with ANSYS finite element analysis software, and the validity of the two models were verified. The results show that it is feasible to establish the LAD finite element model based on cardiac three-dimensional CT images using reverse engineering software. The results of this paper will lay a theoretical foundation for further hemodynamic analysis of LAD.
