Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/ajhb.1310040307 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Relationship between BMI, indicators of lipid metabolism and diabetic neuropathy: a Mendelian randomization study.
Diabetol Metab Syndr
January 2025
First Central Clinical Medical Institute, Tianjin Medical University, Tianjin, China.
Background: To identify the relationship between BMI or lipid metabolism and diabetic neuropathy using a Mendelian randomization (MR) study.
Methods: Body constitution-related phenotypes, namely BMI (kg/m), total cholesterol (TC), and triglyceride (TG), were investigated in this study. Despite the disparate origins of these data, all were accessible through the IEU OPEN GWAS database ( https://gwas.
A machine learning-based model to predict POD24 in follicular lymphoma: a study by the Chinese workshop on follicular lymphoma.
Biomark Res
January 2025
Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003, P.R. China.
Background: Disease progression within 24 months (POD24) significantly impacts overall survival (OS) in patients with follicular lymphoma (FL). This study aimed to develop a robust predictive model, FLIPI-C, using a machine learning approach to identify FL patients at high risk of POD24.
Methods: A cohort of 1,938 FL patients (FL1-3a) from seventeen centers nationwide in China was randomly divided into training and internal validation sets (2:1 ratio).
A prospective, multicenter analysis of the integrated 31-gene expression profile test for sentinel lymph node biopsy (i31-GEP for SLNB) test demonstrates reduced number of unnecessary SLNBs in patients with cutaneous melanoma.
World J Surg Oncol
January 2025
Summit Medical Group, Bend, OR, USA.
Background: National Comprehensive Cancer Network guidelines recommend sentinel lymph node biopsy (SLNB) for patients with > 10% risk of positivity, consider SLNB with 5-10% risk, and foregoing with < 5% risk. The integrated 31-gene expression profile (i31-GEP) algorithm combines the 31-GEP with clinicopathologic variables, estimating SLN positivity risk.
Methods: The i31-GEP SLNB risk prediction accuracy was assessed in patients with T1-T2 tumors enrolled in the prospective, multicenter DECIDE study (n = 322).
Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.
Langenbecks Arch Surg
January 2025
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Background: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic surgery (NOTES) approach has gradually been applied as an emerging minimally invasive approach for the treatment of SSRCs. However, there are no clear indicators for selecting the NOTES approach for patients with SSRCs.
View Article and Find Full Text PDFFlow prediction in sound-based uroflowmetry.
Sci Rep
January 2025
Department of Signal Theory and Communications, Universidad de Valladolid, 47002, Valladolid, Spain.
Sound-based uroflowmetry (SU) offers a non-invasive alternative to traditional uroflowmetry (UF) for evaluating lower urinary tract dysfunctions, enabling home-based testing and reducing the need for clinic visits. This study compares SU and UF in estimating urine flow rate and voided volume in 50 male volunteers (aged 18-60), with UF results from a Minze uroflowmeter as the reference standard. Audio signals recorded during voiding were segmented and machine learning algorithms (gradient boosting, random forest, and support vector machine) estimated flow parameters from three devices: Ultramic384k, Mi A1 smartphone, and Oppo smartwatch.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!