Publications by authors named "M N Charalambides"
: Accurate reconstruction of internal temperature fields from surface temperature data is critical for applications such as non-invasive thermal imaging, particularly in scenarios involving small temperature gradients, like those in the human body. : In this study, we employed 3D convolutional neural networks (CNNs) to predict internal temperature fields. The network's performance was evaluated under both ideal and non-ideal conditions, incorporating noise and background temperature variations.
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- There is a significant risk of reinforcing existing health inequalities in AI health technologies due to biases, primarily stemming from the datasets used.
- The STANDING Together recommendations focus on transparency in health datasets and proactive evaluation of their impacts on different population groups, informed by a comprehensive research process with over 350 global contributors.
- The 29 recommendations are divided into guidance for documenting health datasets and strategies for using them, aiming to identify and reduce algorithmic biases while promoting awareness of the inherent limitations in all datasets.
Article Synopsis
- During the COVID-19 pandemic, AI models were developed to help with health-care resource issues, but previous studies showed that the datasets used often have limitations leading to biased outcomes.
- A systematic review analyzed 192 healthcare datasets from MEDLINE and Google Dataset Search, focusing on metadata completeness, accessibility, and ethical considerations.
- Results indicated significant shortfalls, including that only 48% showed the country of origin, 43% reported age, and under 25% included demographic factors like sex or race, emphasizing the need for improved data quality and transparency to avoid bias in future AI health applications.
This study presents a rigorous mechanical characterisation investigation on milk chocolate with varying porosities, at different temperatures and strain rate levels. Uniaxial compression tests at temperatures varying from 20 °C to 30 °C were performed to measure the bulk properties of chocolate as a function of porosity and temperature. Fracture experiments were also conducted to compute the fracture energy at temperature levels between 20 °C and 30 °C for all tested samples.
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