An enhanced segmentation technique for smokers RBC rouleax coin stacking

Smoking is one of the major factors of having coin stacking formation of Red Blood Cell or commonly known as RBC that can cause blood clots and can lead to stroke. Smokers tends have thicker, high count, and overlapping of RBC compared to non-smokers. Blood cell detection plays significant part in biomedical field. There are two methods in detection of RBC, manual inspection by medical experts and automated machines. The manual inspection process is detection of blood cells under a microscope that is more prone to human error and time consuming, while automated hardware solutions like automated haematology machines are available, due to high cost it is not widely available to poor and developing countries who have a high statistic of smokers. Smokers have a high tendency of overlapping RBC or commonly known as rouleaux coin stacking cell formation. This study presents an enhanced segmentation technique that can detect the high degree of overlapping RBCs of smokers using digital image processing that can be helpful in the medical field

ACORN (A Clinically-Oriented Antimicrobial Resistance Surveillance Network) II: protocol for case based antimicrobial resistance surveillance

Background: Antimicrobial resistance surveillance is essential for empiric antibiotic prescribing, infection prevention and control policies and to drive novel antibiotic discovery. However, most existing surveillance systems are isolate-based without supporting patient-based clinical data, and not widely implemented especially in low- and middle-income countries (LMICs). Methods: A Clinically-Oriented Antimicrobial Resistance Surveillance Network (ACORN) II is a large-scale multicentre protocol which builds on the WHO Global Antimicrobial Resistance and Use Surveillance System to estimate syndromic and pathogen outcomes along with associated health economic costs. ACORN-healthcare associated infection (ACORN-HAI) is an extension study which focuses on healthcare-associated bloodstream infections and ventilator-associated pneumonia. Our main aim is to implement an efficient clinically-oriented antimicrobial resistance surveillance system, which can be incorporated as part of routine workflow in hospitals in LMICs. These surveillance systems include hospitalised patients of any age with clinically compatible acute community-acquired or healthcare-associated bacterial infection syndromes, and who were prescribed parenteral antibiotics. Diagnostic stewardship activities will be implemented to optimise microbiology culture specimen collection practices. Basic patient characteristics, clinician diagnosis, empiric treatment, infection severity and risk factors for HAI are recorded on enrolment and during 28-day follow-up. An R Shiny application can be used offline and online for merging clinical and microbiology data, and generating collated reports to inform local antibiotic stewardship and infection control policies. Discussion: ACORN II is a comprehensive antimicrobial resistance surveillance activity which advocates pragmatic implementation and prioritises improving local diagnostic and antibiotic prescribing practices through patient-centred data collection. These data can be rapidly communicated to local physicians and infection prevention and control teams. Relative ease of data collection promotes sustainability and maximises participation and scalability. With ACORN-HAI as an example, ACORN II has the capacity to accommodate extensions to investigate further specific questions of interest