Epigenetic clocks and gliomas: unveiling the molecular interactions between aging and tumor development

S Chen, Y Jiang, C Wang, S Tong, Y He… - Frontiers in Molecular …, 2024 - frontiersin.org
Gliomas, the most prevalent and aggressive primary brain tumors, represent a diverse group
of malignancies originating from glial cells. These tumors account for significant brain tumor …

A Critical Review on Segmentation of Glioma Brain Tumor and Prediction of Overall Survival

N Rasool, JI Bhat - Archives of Computational Methods in Engineering, 2024 - Springer
In recent years, the surge in glioma brain tumor cases has positioned it as the 10th most
prevalent tumor affecting individuals across diverse age groups. Gliomas, characterized by …

[HTML][HTML] Reproducible and interpretable machine learning-based radiomic analysis for overall survival prediction in glioblastoma multiforme

A Duman, X Sun, S Thomas, JR Powell, E Spezi - Cancers, 2024 - mdpi.com
Simple Summary This study aimed to develop and validate a radiomic model for predicting
overall survival (OS) in glioblastoma multiforme (GBM) patients using pre-treatment MRI …

An Informative Review of Radiomics Studies on Cancer Imaging: The Main Findings, Challenges and Limitations of the Methodologies

R Fusco, V Granata, I Simonetti, SV Setola… - Current …, 2024 - mdpi.com
The aim of this informative review was to investigate the application of radiomics in cancer
imaging and to summarize the results of recent studies to support oncological imaging with …

[HTML][HTML] Radiomics-Based Machine Learning with Natural Gradient Boosting for Continuous Survival Prediction in Glioblastoma

M Karabacak, S Patil, ZC Gersey, RJ Komotar… - Cancers, 2024 - mdpi.com
Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in
adults, with an aggressive disease course that requires accurate prognosis for …

Artificial intelligence in fracture detection on radiographs: a literature review

A Lo Mastro, E Grassi, D Berritto, A Russo… - Japanese Journal of …, 2024 - Springer
Fractures are one of the most common reasons of admission to emergency department
affecting individuals of all ages and regions worldwide that can be misdiagnosed during …

Exploring the prognostic value and biological pathways of transcriptomics and radiomics patterns in glioblastoma multiforme

J Luan, D Zhang, B Liu, A Yang, K Lv, P Hu, H Yu… - Heliyon, 2024 - cell.com
Objectives To develop a multi-omics prognostic model integrating transcriptomics and
radiomics for predicting overall survival in patients with glioblastoma multiforme (GBM), and …

Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment

V Granata, R Fusco, MC Brunese, G Ferrara… - Diagnostics, 2024 - mdpi.com
Purpose: We aimed to assess the efficacy of machine learning and radiomics analysis using
magnetic resonance imaging (MRI) with a hepatospecific contrast agent, in a pre-surgical …

[HTML][HTML] Quantitative Physiologic MRI Combined with Feature Engineering for Developing Machine Learning-Based Prediction Models to Distinguish Glioblastomas …

SA Hosseini, S Servaes, B Hall, S Bhaduri, A Rajan… - Diagnostics, 2024 - mdpi.com
Background: The accurate and early distinction of glioblastomas (GBMs) from single brain
metastases (BMs) provides a window of opportunity for reframing treatment strategies …

Predictive modeling of outcomes in acute leukemia patients undergoing allogeneic hematopoietic stem cell transplantation using machine learning techniques

M Rouzbahani, SA Mousavi, G Hajianfar, A Ghanaati… - Leukemia Research, 2025 - Elsevier
Background Leukemia necessitates continuous research for effective therapeutic
techniques. Acute leukemia (AL) patients undergoing allogeneic hematopoietic stem cell …