Bendable non-silicon RISC-V microprocessor.

Semiconductors have already had a very profound effect on society, accelerating scientific research and driving greater connectivity. Future semiconductor hardware will open up new possibilities in quantum computing, artificial intelligence and edge computing, for applications such as cybersecurity and personalized healthcare. By nature of its ethos, open hardware provides opportunities for even greater collaboration and innovations across education, academic research and industry.

Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology.

ChatGPT and other artificial intelligence (AI) systems have captivated the attention of healthcare providers and researchers for their potential to improve care processes and outcomes. While these technologies hold promise to automate processes, increase efficiency, and reduce cognitive burden, their use also carries risks. In this commentary, we review basic concepts of AI, outline some of the capabilities and limitations of currently available tools, discuss current and future applications in pediatric hematology/oncology, and provide an evaluation and implementation framework that can be used by pediatric hematologist/oncologists considering the use of AI in clinical practice.

Leveraging Resident-As-Teacher Training for Health Equity Education: A Transformative Approach.

: Resident teachers play an essential role in medical education and can support broader efforts to advance anti-racism and health equity in medicine. The Accreditation Council for Graduate Medical Education requires programs to provide education about health care disparities so residents can contribute to and lead work in this area. However, the literature includes few examples, frameworks, or strategies for preparing residents to develop the knowledge and skills needed to promote health equity, including in their role as clinical teachers.

Predictors of adverse outcome in the first and second waves of the COVID-19 pandemic: results from a UK centre.

Background/aims: Data concerning differences in demographics/disease severity between the first and second waves of COVID-19 are limited. We aimed to examine prognosis in patients presenting to hospital with COVID-19 amongst different ethnic groups between the first and second waves in the UK.

Methods: In this retrospective cohort study, we included 1763 patients presenting to a regional hospital centre in Leicester (UK) and compared those in the first ( = 956) and second ( = 807) waves.