Policy Recommendations to Support Equitable Access to Long-Acting Injectables for Human Immunodeficiency Virus Prevention and Treatment: A Policy Paper of the Infectious Diseases Society of America and the HIV Medicine Association.

Long-acting injectables (LAIs) for HIV prevention and treatment could dramatically improve health outcomes and health equity for people with HIV and those who could benefit from pre-exposure prophylaxis. Despite widespread acceptability and demand by providers and potential users of LAIs, implementation has been extremely limited since the introduction of cabotegravir/rilpivirine, the first LAI for HIV treatment, in January 2021, and long-acting cabotegravir, the first LAI for HIV prevention, in December 2021. We report results of a provider survey, conducted by the HIV Medicine Association, which identified LAI implementation barriers related to health insurance processes, staffing and administrative support, drug costs and acquisition, and access for individuals who are uninsured.

Oceanic islands act as drivers for the genetic diversity of marine species: Cardita calyculata (Linnaeus, 1758) in the NE Atlantic as a case-study.

Geographic distribution, as well as evolutionary and biogeographic processes and patterns of marine invertebrate benthic species are strongly shaped by dispersal ability during the life cycle. Remote oceanic islands lie at the brink of complex biotic and abiotic interactions which have significantly influenced the biodiversity patterns we see today. The interaction between geological environmental change and taxon-specific dispersal modes can influence species evolutionary patterns, eventually delimiting species-specific biogeographic regions.

Informing estimates of probability of infection for testing and treatment: expert consensus from a modified-Delphi procedure.

Background: infection (CDI) may be misdiagnosed if testing is performed in the absence of signs or symptoms of disease. This study sought to support appropriate testing by estimating the impact of signs, symptoms, and healthcare exposures on pre-test likelihood of CDI.

Methods: A panel of fifteen experts in infectious diseases participated in a modified UCLA/RAND Delphi study to estimate likelihood of CDI.

Diagnosing Cataracts in the Digital Age: A Survey on AI, Metaverse, and Digital Twin Applications.

Purpose: The study explores the evolving landscape of cataract diagnosis, focusing on both traditional methods and innovative technological integrations. It aims to address challenges with subjectivity in traditional cataract grading and to evaluate how new technologies can enhance diagnostic accuracy and accessibility.

Methods: The research introduces and examines the use of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in automating and improving cataract screening processes.

Examining different cost ratio frameworks for decision rule machine learning algorithms in diagnostic application.

Background: Artificial Intelligence (AI) plays a pivotal role in the diagnosis of health conditions ranging from general well-being to critical health issues. In the realm of health diagnostics, an often overlooked but critical aspect is the consideration of cost-sensitive learning, a facet that this study prioritizes over the non-invasive nature of the diagnostic process whereas the other standard metrics such as accuracy and sensitivity reflect weakness in error profile.

Objective: This research aims to investigate the total cost of misclassification (Total Cost) by decision rule Machine Learning (ML) algorithms implemented in Java platforms such as DecisionTable, JRip, OneR, and PART.