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Trends of trauma team physicians toward patients with bleeding in Saudi Arabia: a cross-sectional study.
Hosp Pract (1995)
December 2024
Radiodiagnostics and Medical Imaging Department, King Fahd Military Medical Complex, Dhahran, Eastern, Saudi Arabia.
Objectives: Trauma poses a significant health burden in Saudi Arabia, with high rates of morbidity and mortality rates. We evaluated the trends among trauma team (TT) physicians in Saudi Arabia regarding their awareness and referral practices for percutaneous endovascular arterial embolization (EAE) in bleeding patients.
Methods: A 13-question survey developed by consultants from various specialties assessed the knowledge of TT physicians regarding decision-making and appropriate approaches for managing traumatic bleeding.
Development and validation of a MRI-radiomics-based machine learning approach in High Grade Glioma to detect early recurrence.
Front Oncol
November 2024
Department of Neurosurgery, Mater Olbia Hospital, Olbia, Italy.
Purpose: Patients diagnosed with High Grade Gliomas (HGG) generally tend to have a relatively negative prognosis with a high risk of early tumor recurrence (TR) after post-operative radio-chemotherapy. The assessment of the pre-operative risk of early versus delayed TR can be crucial to develop a personalized surgical approach. The purpose of this article is to predict TR using MRI radiomic analysis.
View Article and Find Full Text PDFNatural History from Appendiceal Mucocele to Jelly Belly.
Diagnostics (Basel)
November 2024
1st Department of Surgery, General University Hospital Prague, 128 00 Prague, Czech Republic.
Article Synopsis
- Mucocele of the appendix and pseudomyxoma peritonei are uncommon conditions with vague early symptoms.
- The complications of these diseases can include perforation of the appendix and widespread abdominal involvement, often referred to as "jelly belly."
- This text outlines the typical progression and clinical presentations associated with these conditions over time.
Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies.
Diagnostics (Basel)
November 2024
Radiology Department, ASST Fatebenefratelli Sacco, Piazza Principessa Clotilde 3, 20121 Milan, Italy.
Although radiomics research has experienced rapid growth in recent years, with numerous studies dedicated to the automated extraction of diagnostic and prognostic information from various imaging modalities, such as CT, PET, and MRI, only a small fraction of these findings has successfully transitioned into clinical practice. This gap is primarily due to the significant methodological challenges involved in radiomics research, which emphasize the need for a rigorous evaluation of study quality. While many technical aspects may lie outside the expertise of most radiologists, having a foundational knowledge is essential for evaluating the quality of radiomics workflows and contributing, together with data scientists, to the development of models with a real-world clinical impact.
View Article and Find Full Text PDFComprehensive analysis of transcriptomics and radiomics revealed the potential of TEDC2 as a diagnostic marker for lung adenocarcinoma.
PeerJ
November 2024
Respiratory Department, The 900 Hospital of the Joint Service Support Force of the People's Liberation Army of China, Fuzhou, China.
Background: Lung adenocarcinoma (LUAD) is a widely occurring cancer with a high death rate. Radiomics, as a high-throughput method, has a wide range of applications in different aspects of the management of multiple cancers. However, the molecular mechanism of LUAD by combining transcriptomics and radiomics in order to probe LUAD remains unclear.
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