A feasibility study on utilizing machine learning technology to reduce the costs of gastric cancer screening in Taizhou, China.

Aim: To optimize gastric cancer screening score and reduce screening costs using machine learning models.

Methods: This study included 228,634 patients from the Taizhou Gastric Cancer Screening Program. We used three machine learning models to optimize Li's gastric cancer screening score: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), and Deep Learning (DL).

Qualitative study on the perception of good death in patients with end-stage cancer in oncology nurses.

Objective: To explore the perception of good death of patients with end-stage cancer by nurses in the oncology department.

Method: In the study we used a phenomenological approach and semi-structured interviews. A total of 11 nurses from the oncology department of a Grade A hospital in Taizhou were interviewed on the cognition of good death from July 1 to September 30, 2022.

Relationship between the microenvironment and survival in kidney transplantation: a bibliometric analysis from 2013 to 2023.

Background: Kidney transplantation is considered the most effective treatment for end-stage renal failure. Recent studies have shown that the significance of the immune microenvironment after kidney transplantation in determining prognosis of patients. Therefore, this study aimed to conduct a bibliometric analysis to provide an overview of the knowledge structure and research trends regarding the immune microenvironment and survival in kidney transplantation.

Anoikis-related signature identifies tumor microenvironment landscape and predicts prognosis and drug sensitivity in colorectal cancer.

Anoikis, a mechanism of programmed apoptosis, plays an important role in growth and metastasis of tumors. However, there are still few available comprehensive reports on the impact of anoikis on colorectal cancer. A clustering analysis was done on 133 anoikis-related genes in GSE39582, and we compared clinical features between clusters, the tumor microenvironment was analyzed with algorithms such as "Cibersort" and "ssGSEA".

New hope for esophageal stricture prevention: A prospective single-center trial on acellular dermal matrix.

Background: Given the high incidence of esophageal cancer in China, an increasing number of patients there are undergoing endoscopic mucosal dissection (ESD). Although the 5-year survival rate after ESD can exceed 95%, esophageal stricture, the most common and serious postoperative complication, affects the long-term prognosis of patients and the quality of life. Autologous mucosal grafts have proven to be successful in preventing stricture after ESD for early esophageal cancer.

Developing a Prognostic Model for Primary Biliary Cholangitis Based on a Random Survival Forest Model.

Primary biliary cholangitis (PBC) is a rare autoimmune liver disease with few effective treatments and a poor prognosis, and its incidence is on the rise. There is an urgent need for more targeted treatment strategies to accurately identify high-risk patients. The use of stochastic survival forest models in machine learning is an innovative approach to constructing a prognostic model for PBC that can improve the prognosis by identifying high-risk patients for targeted treatment.

Correlation study between motor rehabilitation level and psychological state in patients with limb movement disorders after stroke.

Background: The psychological state of patients with post stroke limb movement disorders undergoes a series of changes that affect rehabilitation training and recovery of limb motor function.

Aim: To determine the correlation between motor rehabilitation and the psychological state of patients with limb movement disorders after stroke.

Methods: Eighty patients with upper and lower limb dysfunction post stroke were retrospectively enrolled in our study.

Development and validation of LightGBM algorithm for optimizing of Helicobacter pylori antibody during the minimum living guarantee crowd based gastric cancer screening program in Taizhou, China.

Gastric cancer continues to be a significant health concern in China, with a high incidence rate. To mitigate its impact, early detection and treatment is key. However, conducting large-scale endoscopic gastric cancer screening is not feasible in China.

Effectiveness and safety of endoscopic resection for duodenal gastrointestinal stromal tumors: A single center analysis.

Background: Endoscopic resection for duodenal gastrointestinal stromal tumors (GISTs) is still considered a great challenge with a high risk of complications, including perforation, bleeding, tumor rupture, and residual tumor.

Aim: To assess the effectiveness and safety of endoscopic resection for duodenal GISTs.

Methods: Between January 2010 and January 2022, 11 patients with duodenal GISTs were treated with endoscopic resection.

Association Between Asymmetry of Substantia Nigra Hyperechogenicity and Clinical Characteristics in Different Parkinson Disease Subtypes: A 5-Year Follow-up Study.

Our study focused on three aspects to determine whether bilateral substantia nigra hyperechogenicity (SN+) is asymmetrical, whether the asymmetry of SN+ is related to the clinical features and whether there is variation in SN+ asymmetry during the progression of Parkinson disease (PD). This follow-up study included 234 patients with PD, who were divided into tremor PD (TD, n = 67) and non-tremor PD (NTD, n = 167) groups based on the Unified Parkinson's Disease Rating Scale (UPDRS) Part III. All participants underwent transcranial sonography (TCS) and clinical assessment.

The Feasibility of Applying Artificial Intelligence to Gastrointestinal Endoscopy to Improve the Detection Rate of Early Gastric Cancer Screening.

Convolutional neural networks in the field of artificial intelligence show great potential in image recognition. It assisted endoscopy to improve the detection rate of early gastric cancer. The 5-year survival rate for advanced gastric cancer is less than 30%, while the 5-year survival rate for early gastric cancer is more than 90%.

Shear wave elastography characteristics of upper limb muscle in rigidity-dominant Parkinson's disease.

Background: Rigidity is one of the major manifestations of Parkinson's disease (PD), but no quantitative and objective imaging method has been developed to measure rigidity. Ultrasound shear wave elastography (SWE) can reflect the stiffness of tissue by providing a quantitative index. Thus, we conducted this study to evaluate the potential clinical value of SWE in assessing rigidity in PD.

[Inhibitory effects of doxycycline on argyrophilic nucleolar organizing regions and a-smooth muscle actin expression in proliferative bovine corneal myofibroblasts in vitro].

Objective: To investigate the effect of doxycycline on the nucleolar organizing regions and a-smooth muscle actin expression in bovine corneal myofibroblasts in vitro and assess its contribution to ocular surface repair mechanisms.

Methods: Cell culture and identification: bovine corneal fibroblasts were cultured after the stroma was incubated in 1.0 and 2.