Enhancing mammography: a comprehensive review of computer methods for improving image quality.

Mammography imaging remains the gold standard for breast cancer detection and diagnosis, but challenges in image quality can lead to misdiagnosis, increased radiation exposure, and higher healthcare costs. This comprehensive review evaluates traditional and machine learning-based techniques for improving mammography image quality, aiming to benefit clinicians and enhance diagnostic accuracy. Our literature search, spanning 2015 - 2024, identified 115 articles focusing on contrast enhancement and noise reduction methods, including histogram equalization, filtering, unsharp masking, fuzzy logic, transform-based techniques, and advanced machine learning approaches.

A pioneering longterm experiment on mesophotic macrofouling communities in the North Atlantic.

The mesophotic zone represents one of our planet's largest and least explored biomes. An increasing number of studies evidence the importance of macrofouling species in marine ecosystems, but information on these communities and the factors influencing their structures at mesophotic depths remain poor. This lack of understanding limits our ability to predict anthropogenic impacts or conduct restoration operations in the mesophotic and the lower boundary of the euphotic zones.

Comparative analysis of treatment modalities for solitary, small (≤3 cm) hepatocellular carcinoma: A systematic review and network meta-analysis of oncologic outcomes.

Background: Solitary hepatocellular carcinoma measuring ≤3 cm represents approximately 30% of hepatocellular carcinoma cases, yet treatment guidelines lack robust evidence. This study compares oncologic outcomes after ablation, liver resection, and liver transplantation for solitary, small hepatocellular carcinoma.

Methods: We systematically searched databases up to 7 February 2022, for studies including adults with solitary hepatocellular carcinoma ≤3 cm treated by any ablation, liver resection, or liver transplantation.

The role of disease modifying therapies in late-onset multiple sclerosis: A Portuguese multicentric characterization study.

Introduction: Knowledge about the effect of disease modifying treatment (DMT) in late-onset multiple sclerosis (LOMS, onset ≥50 years-old) is scarce. This study aims to evaluate the association between DMT use and multiple sclerosis (MS) evolution in a LOMS cohort.

Methods: This multicentre, retrospective and observational study included LOMS patients with ≥2 years of follow-up.

Alleviation of COVID-19 Symptoms and Reduction in Healthcare Utilization Among High-Risk Patients Treated With Nirmatrelvir/Ritonavir (NMV/R): A phase 3 randomized trial.

Background: Nirmatrelvir/ritonavir (NMV/r) is an oral antiviral treatment for mild to moderate COVID-19.

Methods: This phase 2/3, double-blind, randomized (1:1) study assessed oral NMV/r 300 mg/100 mg versus placebo every 12 hours for 5 days in high-risk, unvaccinated, nonhospitalized, symptomatic adults with COVID-19 from 343 sites across 21 countries. In testing the primary endpoint of COVID-19‒related hospitalization and all-cause deaths and key secondary endpoints including symptom duration and COVID-19‒related medical visits, Type I error was controlled with prespecified sequential testing and the Hochberg procedure.