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http://dx.doi.org/10.1182/bloodadvances.2023012090 | DOI Listing |
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFArq Bras Cir Dig
September 2025
Universidade de São Paulo, Faculty of Medicine, Department of Gastroenterology, Colonoscopy Division - São Paulo (SP), Brazil.
Background: Artificial intelligence (AI)-assisted colonoscopy has emerged as a tool to enhance adenoma detection rates (ADRs) and improve lesion characterization. However, its performance in real-world settings, especially in developing countries, remains uncertain.
Aims: The aim of this study was to evaluate the impact of AI on ADRs and its concordance with histopathological diagnosis.
Braz J Biol
September 2025
Faculty of Rehabilitation & Allied Health Sciences - FRAHS, Riphah International University, Rawalpindi, Pakistan.
Antimicrobial resistance (AMR) is a significant public health concern globally, and Pakistan is no exception. The misuse and overuse of antibiotics, inadequate regulation of their sale, and a lack of awareness contribute to the rising levels of AMR in the country. study presents a detailed analysis of blood and urine samples collected in Pakistan over various periods, focusing on pathogen prevalence, gender distribution, and age-wise patterns.
View Article and Find Full Text PDFPLoS Comput Biol
September 2025
Division of Applied Mathematics, Brown University, Providence, Rhode Island, United States of America.
Gaucher Disease (GD) is a rare genetic disorder characterized by a deficiency in the enzyme glucocerebrosidase, leading to the accumulation of glucosylceramide in various cells, including red blood cells (RBCs). This accumulation results in altered biomechanical properties and rheological behavior of RBCs, which may play an important role in blood rheology and the development of bone infarcts, avascular necrosis (AVN) and other bone diseases associated with GD. In this study, dissipative particle dynamics (DPD) simulations are employed to investigate the biomechanics and rheology of blood and RBCs in GD under various flow conditions.
View Article and Find Full Text PDFPLoS One
September 2025
School of Computer Science, CHART Laboratory, University of Nottingham, Nottingham, United Kingdom.
Background And Objective: Male fertility assessment through sperm morphology analysis remains a critical component of reproductive health evaluation, as abnormal sperm morphology is strongly correlated with reduced fertility rates and poor assisted reproductive technology outcomes. Traditional manual analysis performed by embryologists is time-intensive, subjective, and prone to significant inter-observer variability, with studies reporting up to 40% disagreement between expert evaluators. This research presents a novel deep learning framework combining Convolutional Block Attention Module (CBAM) with ResNet50 architecture and advanced deep feature engineering (DFE) techniques for automated, objective sperm morphology classification.
View Article and Find Full Text PDF