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Breast cancer is now the most deadly cancer worldwide. Mammography screening is the most effective method for early detection and diagnosis of breast cancer. Due to the lack of labeled mammograms, building an AI system for mammography screening often relies heavily on human-designed data augmentation, which doesn't always perform robustly when applied to clinical scenarios. This paper presents a novel framework of Supervised Contrastive Pre-training followed by Supervised Fine-tuning (SCP+SF) for mammography screening. Unlike the previous approaches, the proposed supervised contrastive pre-training does not need a data augmentation module. We apply the SCP+SF framework to two challenging and important mammography screening tasks for breast cancer: mammographic abnormality screening and mammographic malignancy screening. Our extensive experiments on a large-scale dataset show that the supervised contrastive pre-training (SCP) can substantially improve the final model performance compared with the traditional direct supervised training approach. Superior results of AUC and specificity/sensitivity have been achieved on two clinically significant mammographic screening tasks in comparison with previously reported State-Of-The-Art approaches. We believe this work is the first to show that supervised contrastive pre-training (SCP) followed by supervised fine-tuning (SF) can outperform the supervised counterpart on these two critical medical imaging tasks. [ABSTRACT FROM AUTHOR]

By generating almost 5% of the world's carbon emissions, healthcare, if it were a country, would be the world's fifth biggest polluter and for the UK in 2017, the health sector alone was responsible for 4.4% of its net global greenhouse gas emissions and 6.3% of that country's carbon footprint. In 2020, the UK National Health Service became the first health service to announce its intention to achieve Net Zero emissions. Between 20% and 33% of health care waste is thought to originate from a hospital's operating rooms and up to 90% of this is sent for unnecessary hazardous-waste disposal. Current practice allows the use of disposable or re-usable textile items but textile products can still account for up to 30% of the waste generated within an operating theatre. This paper explains the steps that those working in textile product development and those working in healthcare can take to reduce the textile-related carbon footprint and, in particular, to how medical textile items, such as gowns and drapes can be selected to produce a lower carbon footprint. Attention is also paid to how reusable textiles can be microbiologically decontaminated and laundered in the most economical and ecologically-acceptable fashion. The paper draws attention to the need for willingness to implement already-existing solutions for environmentally-acceptable personal protective equipment (PPE) and low carbon-footprint laundry processes for the cleaning and microbiological decontamination of all types of re-usable textiles employed within the operating theatre. Where redesign of PPE is required, the need is stressed for sensitive adjustment of standards to support the implementation of reusable forms, whilst maintaining the original high performance requirements expected in actual use. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to assess National Health Service (NHS) decision-making protocols during the pandemic, with two primary objectives: (1) to establish whether decision-making protocols changed during the pandemic and (2) to evaluate if these changes could inform future decision-making strategies beyond the pandemic. By focusing on the shift from traditional to emergency decision-making processes, this research seeks to derive actionable insights for enhancing policy and practice in crisis conditions. Design/methodology/approach: We employ a mixed-methods approach, gathering data through an online survey targeted at senior NHS decision-makers involved in the pandemic response. Our survey collected quantitative and qualitative data to assess changes in decision-making protocols. The analysis included statistical techniques to quantify changes and thematic analysis to explore their implications, providing a detailed understanding of decision-making adaptations during the crisis and their potential future impact. Findings: Our findings clarify the role of the NHS values and constitution, which prioritize patient welfare, dignity and equitable access to healthcare, guiding all decision-making. During the pandemic, the urgency to respond swiftly necessitated modifications to these guiding principles. Traditional processes were adapted, allowing for more rapid decision-making while still aligning with the core values, effectively balancing immediate response needs with long-term healthcare commitments. Research limitations/implications: Our research contributes to decision-making under crisis conditions within a healthcare context and brings together a theoretical background which has accommodated the development of models and approaches that can be utilized by both service and manufacturing organizations. In addition, we have sought to bring together the importance of decision-making protocols under crisis conditions using observations from respondents who experienced decision-making at a senior level prior, during and beyond the period of the COVID-19 pandemic, which has assisted in the models developed in this paper. In addition, our empirical research demonstrates the importance that the values of the organization have upon decision-making and how such values need to be adjusted in the light of crisis operations. Practical implications: Our research provides insightful observations relating to the pressures upon decision-making protocols under crisis conditions and provides senior decision-makers with an approach to realigning values to cope with unusual and highly pressurized operating environments. Notably, there is a clear requirement for decision-makers to communicate clearly to staff the need to temporarily alter the modus operandi to reflect crisis operations. Originality/value: To the best of the authors' knowledge, this is the first study to explore decision-making in the NHS during a pandemic and to clearly demonstrate how such decision-making needs to be adapted to reflect the nature and scope of delivering a complex healthcare service under crisis conditions. [ABSTRACT FROM AUTHOR]