A Hybrid Transformer-Convolutional Neural Network for Segmentation of Intracerebral Hemorrhage and Perihematomal Edema on Non-Contrast Head Computed Tomography (CT) with Uncertainty Quantification to Improve Confidence.

Intracerebral hemorrhage (ICH) and perihematomal edema (PHE) are key imaging markers of primary and secondary brain injury in hemorrhagic stroke. Accurate segmentation and quantification of ICH and PHE can help with prognostication and guide treatment planning. In this study, we combined Swin-Unet Transformers with nnU-NETv2 convolutional network for segmentation of ICH and PHE on non-contrast head CTs.

Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT).

: Intracerebral hemorrhages (ICH) and perihematomal edema (PHE) are respective imaging markers of primary and secondary brain injury in hemorrhagic stroke. In this study, we explored the potential added value of PHE radiomic features for prognostication in ICH patients. : Using a multicentric trial cohort of acute supratentorial ICH ( = 852) patients, we extracted radiomic features from ICH and PHE lesions on admission non-contrast head CTs.

Efficacy of Prophylactic Antibiotics in COPD: A Systematic Review.

: Chronic obstructive pulmonary disease (COPD) is a global health problem and the third leading contributor to mortality worldwide. This systematic review aims to summarize the results of previous studies tackling the question of the efficacy of long-term prophylaxis of antibiotics in COPD patients, with particular regard to exacerbation rate, time to first exacerbation, health status, airway bacterial load, inflammatory markers, cell counts in sputum samples, and potential adverse events. : Four studies found significant improvement in the exacerbation rate in patients receiving antibiotic intervention.

Validation of AI-driven measurements for hip morphology assessment.

Rationale And Objectives: Accurate assessment of hip morphology is crucial for the diagnosis and management of hip pathologies. Traditional manual measurements are prone to mistakes and inter- and intra-reader variability. Artificial intelligence (AI) could mitigate such issues by providing accurate and reproducible measurements.

Erratum: Lipid nanoparticle encapsulation of a Delta spike-CD40L DNA vaccine improves effectiveness against Omicron challenge in Syrian hamsters.

[This corrects the article DOI: 10.1016/j.omtm.