Publications by authors named "Meijiao Jiang"
Background: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA).
Methods: This retrospective study included 413 patients hospitalized at Xinhua hospital diagnosed with SP from June 1, 2015 to May 30, 2020.
Article Synopsis
- Deep learning (DL) algorithms can enhance the classification of ovarian tumors by analyzing multimodal ultrasound (US) images, aiming to differentiate between benign and malignant tumors.
- The study involved 422 women with a mix of benign and malignant tumors, where the data was split for training, validation, and testing, and comparisons were made against the Ovarian-Adnexal Reporting and Data System (O-RADS) and expert assessments.
- Results showed that DL algorithms achieved a similar level of accuracy in detecting malignancy (AUC of 0.93) compared to O-RADS (0.92) and expert assessments (0.97), indicating that DL can be a reliable tool for ovarian tumor classification.
A simple and sensitive electrochemical cholesterol biosensor was fabricated based on ceramic-coated liposome (cerasome) and graphene quantum dots (GQDs) with good conductivity. The cerasome consists of a lipid-bilayer membrane and a ceramic surface as a soft biomimetic interface, and the mild layer-by-layer self-assembled method as the immobilization strategy on the surface of the modified electrode was used, which can provide good biocompatibility to maintain the biological activity of cholesterol oxidase (ChOx). The GQDs promoted electron transport between the enzyme and the electrode more effectively.
View Article and Find Full Text PDFAim: This study aimed to compare different ultrasound-based International Ovarian Tumor Analysis (IOTA) prediction models, namely, the Simple Rules (SRs) the Assessment of Different NEoplasias in the adneXa (ADNEX) models, and the Risk of Malignancy Index (RMI), for the pre-operative diagnosis of adnexal mass.
Methods: This single-centre diagnostic accuracy study involved 486 patients. All ultrasound examinations were analyzed and the prediction models were applied.
Background: Ovarian sex cord stromal tumours (OSCSTs) are rare ovarian tumours and include different histopathologic subtypes. This study aimed to analyse the clinical and sonographic characteristics of different histopathologic OSCST subtypes.
Methods: A total of 63 patients with surgically proven OSCSTs were enrolled in this retrospective study to analyse their clinical and sonographic features.
The L. () is commonly used as a traditional medicine, and its antitumor effects have also been studied. However, the functional roles of flavonoids in in antitumor activities have not been clarified.
View Article and Find Full Text PDFThe flavonoids in L. have been used in traditional medicine due to its anti-inflammatory and antibacterial properties. However, the specific mechanism of its antibacterial effect, and the potential therapeutic effect on vaginitis have not been well explained.
View Article and Find Full Text PDFBackground: Ovarian thecoma-fibroma groups (OTFG) are uncommon sex cord-stromal neoplasms. The objective of the study was to demonstrate clinical and sonographic features of OTFG and compare with surgical histopathology.
Methods: A total of 61 patients with surgically proven OTFG were enrolled in this retrospective study to demonstrate its clinical and sonographic features and to compare with pathological findings.