Triaging mammography with artificial intelligence: an implementation study.

Purpose: Many breast centers are unable to provide immediate results at the time of screening mammography which results in delayed patient care. Implementing artificial intelligence (AI) could identify patients who may have breast cancer and accelerate the time to diagnostic imaging and biopsy diagnosis.

Methods: In this prospective randomized, unblinded, controlled implementation study we enrolled 1000 screening participants between March 2021 and May 2022.

Vaccination coverage, vaccine hesitancy and factors associated with incomplete vaccination: a household survey conducted with children born between 2017 and 2018 in the inland municipalities of Northeastern Brazil.

Objective: To analyze vaccination coverage and factors associated with incomplete vaccination in inland municipalities of Northeastern Brazil.

Methods: This was a household survey using cluster sampling conducted in Vitória da Conquista, Bahia state, Caruaru, Pernambuco state, Sobral, Ceará state and Imperatriz, Maranhão state between 2020 and 2022. Vaccination coverage by valid doses and vaccine hesitancy were analyzed, with the odds ratio (OR) estimated and adjusted using logistic regression.

Vaccination coverage and factors associated with incomplete polio vaccine schedule in children born in 2017-2018, in state capitals and interior region municipalities of Northeast Brazil.

Objective: To analyse vaccination coverage and factors associated with incomplete polio vaccination in a cohort of children born in 2017-2018, in state capitals and interior region municipalities of Northeast Brazil.

Methods: Household survey of children aged ≤24 months conducted between 2020 and 2022. Vaccination coverage and dropout rates were estimated, as well as factors associated with incomplete vaccination, analyzed by calculating odds ratios (OR) and 95% confidence intervals (95%CI).

Fault Detection and Diagnosis in Industry 4.0: A Review on Challenges and Opportunities.

Integrating Machine Learning (ML) in industrial settings has become a cornerstone of Industry 4.0, aiming to enhance production system reliability and efficiency through Real-Time Fault Detection and Diagnosis (RT-FDD). This paper conducts a comprehensive literature review of ML-based RT-FDD.

Inflammatory discoveries two years after acute severe COVID-19: a longitudinal biomarker profile assessment in long COVID individuals in the Brazilian Amazon.

Background: In SARS-CoV-2 infection, cytokines and laboratory biomarkers play a key role in disease progression and their long-term levels have been associated with the outcome of long COVID-19.

Objectives: I) study the levels of cytokines, hematological and biochemical biomarkers in the acute and post-acute phases of COVID-19 disease; and II) assess the impact of COVID-19 vaccine doses on fatigue symptoms.

Methods: This study is an exploratory cohort nested within a clinical and laboratory follow-up of surviving participants after pre-vaccine acute COVID-19 infection with severe clinical manifestations.