Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/s1045-1056(03)00039-3 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.
Lung Cancer
January 2025
Internal Medicine III, Wakayama Medical University, Wakayama, Japan.
Objectives: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through comprehensive gene expression analysis using machine learning (ML).
Methods: A prospective multicenter cohort of patients with ES-SCLC who received first-line chemo-immunotherapy was analyzed.
Targeted Next-Generation Sequencing of Cell-Free DNA to Detect -Immunoglobulin Translocation and Epstein-Barr Virus DNA in Plasma of Burkitt Lymphoma Patients in East Africa.
JCO Glob Oncol
January 2025
University of Oxford, Oxford, United Kingdom.
Purpose: Epstein-Barr virus (EBV)-positive Burkitt lymphoma (BL) affects children in sub-Saharan Africa, but diagnosis via tissue biopsy is challenging. We explored a liquid biopsy approach using targeted next-generation sequencing to detect the -immunoglobulin (-Ig) translocation and EBV DNA, assessing its potential for minimally invasive BL diagnosis.
Materials And Methods: The panel included targets for the characteristic -Ig translocation, mutations in intron 1 of , mutations in exon 2 of , and three EBV genes: EBV-encoded RNA (EBER)1, EBER2, and EBV nuclear antigen 2.
Non-Invasive Assessment of VEGF and Prognosis in Gastric Cancer through Radiomic Features.
Clin Transl Gastroenterol
December 2024
Department of Radiation Oncology, Wake Forest University School of Medicine, Winston-Salem, NC 27157, USA.
Introduction: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with delayed diagnosis often limiting effective treatment options. This study introduces a novel, non-invasive radiomics-based approach utilizing [18F] FDG PET/CT to predict VEGF status and survival in GC patients. The ability to non-invasively assess these parameters can significantly influence therapeutic decisions and outcomes.
View Article and Find Full Text PDFComprehensive Analysis of Factors Influencing Patients' Preferences and Attitudes toward Dental Treatment Choices.
Ann Afr Med
December 2024
Department of Public Health Dentistry, Government Dental College, Kottayam, Kerala, India.
Introduction: In recent years, patient preferences and attitudes have become crucial in shaping dental treatment choices and service utilization. Understanding these preferences is crucial for improving service delivery and patient satisfaction.
Aim: This study aims to comprehensively analyze the factors influencing these preferences, focusing on demographic, socio-economic, and behavioral variables, and the growing role of social media in healthcare decisions.
Performance evaluation and comparative analysis of different machine learning algorithms in predicting postnatal care utilization: Evidence from the ethiopian demographic and health survey 2016.
PLOS Digit Health
January 2025
Department of Health Informatics, School of Public Health, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Postnatal care refers to the support provided to mothers and their newborns immediately after childbirth and during the first six weeks of life, a period when most maternal and neonatal deaths occur. In the 30 countries studied, nearly 40 percent of women did not receive a postpartum care check-up. This research aims to evaluate and compare the effectiveness of machine learning algorithms in predicting postnatal care utilization in Ethiopia and to identify the key factors involved.
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!