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Chronic hepatitis B virus (CHB) infection remains a major global health burden and the non-invasive and accurate diagnosis of significant liver fibrosis (≥ F2) in CHB patients is clinically very important. This study aimed to assess the potential of the joint use of ultrasound images of liver parenchyma, liver stiffness values, and patients' clinical parameters in a deep learning model to improve the diagnosis of ≥ F2 in CHB patients.Of 527 CHB patients who underwent US examination, liver elastography and biopsy, 284 eligible patients were included. We developed a deep learning-based data integration network (DI-Net) to fuse the information of ultrasound images of liver parenchyma, liver stiffness values and patients' clinical parameters for diagnosing ≥ F2 in CHB patients. The performance of DI-Net was cross-validated in a main cohort (n = 155) of the included patients and externally validated in an independent cohort (n = 129), with comparisons against single-source data-based models and other non-invasive methods in terms of the area under the receiver-operating-characteristic curve (AUC).DI-Net achieved an AUC of 0.943 (95% confidence interval [CI] 0.893-0.973) in the cross-validation, and an AUC of 0.901 (95% CI 0.834-0.945) in the external validation, which were significantly greater than those of the comparative methods (AUC ranges: 0.774-0.877 and 0.741-0.848 for cross- and external validations, respectively, pThe joint use of ultrasound images of liver parenchyma, liver stiffness values, and patients' clinical parameters in a deep learning model could significantly improve the diagnosis of ≥ F2 in CHB patients.

Background The clinical application of robotic-assisted gastrectomy remains controversial, especially as clinical studies of this operation navigated by carbon nanoparticle suspension injection (CNSI) have not been conducted. This study aims to assess the perioperative safety and efficacy of CNSI-guided robotic-assisted gastrectomy in patients with gastric cancer by focusing on short-term outcomes. Methods A retrospective analysis of patients who underwent CNSI-guided laparoscopic or robotic-assisted gastrectomy with a pathological diagnosis of gastric cancer was conducted. Data on demographics, surgical management, clinical-pathological results and short-term outcomes were compared among the groups. Results A total of 126 eligible patients were separated into the robotic-assisted gastrectomy (RAG) group (n = 16) and the laparoscopic gastrectomy (LG) group (n = 110) in total. The operation time of the RAG group is longer than the LG group (p = 0.0000). When it comes to perioperative and short-term complications, there exists no statistical difference between the two groups. Conclusion The time required for CNSI-guided robotic-assisted gastrectomy is longer than that for CNSI-guided laparoscopic gastrectomy. CNSI-guided robotic-assisted gastrectomy is safe and effective.

In this paper, we study the positive periodic solutions of a kind of p-Laplacian neutral differential equation with a singularity. By applying the continuation theorem and some analytic techniques, we shall establish several new criteria for the existence of positive periodic solutions for the considered problem. Some recent results in the literature are generalized and improved. Three examples are given to illustrate the effectiveness of our results.