Whole lung radiomic features are associated with overall survival in patients with locally advanced non-small cell lung cancer treated with definitive radiotherapy.

Background: Several studies have suggested that lung tissue heterogeneity is associated with overall survival (OS) in lung cancer. However, the quantitative relationship between the two remains unknown. The purpose of this study is to investigate the prognostic value of whole lung-based and tumor-based radiomics for OS in LA-NSCLC treated with definitive radiotherapy.

A scoping review of the Trauma Recovery Center model for underserved victims of violent crime.

Victimization in the United States is common and has long lasting negative impacts for individuals, often disproportionately impacting those of color and from low socioeconomic communities. The Trauma Recovery Center (TRC) model aims to provide comprehensive mental health and wrap-around case management services for underserved victims of crime. Following PRISMA-ScR guidelines, we sought to further our knowledge about the impact of the TRC model.

Actionability of Synthetic Data in a Heterogeneous and Rare Health Care Demographic: Adolescents and Young Adults With Cancer.

Purpose: Research on rare diseases and atypical health care demographics is often slowed by high interparticipant heterogeneity and overall scarcity of data. Synthetic data (SD) have been proposed as means for data sharing, enlargement, and diversification, by artificially generating real phenomena while obscuring the real patient data. The utility of SD is actively scrutinized in health care research, but the role of sample size for actionability of SD is insufficiently explored.

The anatomical basis for surgical intervention in myositis ossificans-A systematic review.

Myositis ossificans (MO) is a benign condition characterized by heterotrophic bone formation, most commonly within muscle tissue. Multiple types have been described, the most predominant being myositis ossificans circumscripta, which occurs in response to trauma. Myositis ossificans cases reported in the literature were reviewed systematically.

Artificial intelligence research in radiation oncology: a practical guide for the clinician on concepts and methods.

The use of artificial intelligence (AI) holds great promise for radiation oncology, with many applications being reported in the literature, including some of which are already in clinical use. These are mainly in areas where AI provides benefits in efficiency (such as automatic segmentation and treatment planning). Prediction models that directly impact patient decision-making are far less mature in terms of their application in clinical practice.