Machine Learning Approach for the Early Prediction of the Risk of Overweight and Obesity in Young People

Obesity is a major global concern with more than 2.1 billion people overweight or obese worldwide which amounts to almost 30% of the global population. If the current trend continues, the overweight and obese population is likely to increase to 41% by 2030. Individuals developing signs of weight gain or obesity are also at a risk of developing serious illnesses such as type 2 diabetes, respiratory problems, heart disease and stroke. Some intervention measures such as physical activity and healthy eating can be a fundamental component to maintain a healthy lifestyle. Therefore, it is absolutely essential to detect childhood obesity as early as possible. This paper utilises the vast amount of data available via UK’s millennium cohort study in order to construct a machine learning driven model to predict young people at the risk of becoming overweight or obese. The childhood BMI values from the ages 3, 5, 7 and 11 are used to predict adolescents of age 14 at the risk of becoming overweight or obese. There is an inherent imbalance in the dataset of individuals with normal BMI and the ones at risk. The results obtained are encouraging and a prediction accuracy of over 90% for the target class has been achieved. Various issues relating to data preprocessing and prediction accuracy are addressed and discussed

Surfing the spectrum - what is on the horizon?

Diagnostic imaging techniques have evolved with technological advancements - but how far? The objective of this article was to explore the electromagnetic spectrum to find imaging techniques which may deliver diagnostic information of equal, or improved, standing to conventional radiographs and to explore any developments within radiography which may yield improved diagnostic data. A comprehensive literature search was performed using Medline, Web of Knowledge, Science Direct and PubMed Databases. Boolean Operators were used and key-terms included (not exclusively): terahertz, X-ray, ultraviolet, visible, infra-red, magnetic resonance, dental, diagnostic, caries and periodontal. Radiographic techniques are primarily used for diagnostic imaging in dentistry, and continued developments in X-ray imaging include: phase contrast, darkfield and spectral imaging. Other modalities have potential application, for example, terahertz, laser doppler and optical techniques, but require further development. In particular, infra-red imaging has regenerated interest with caries detection in vitro, due to improved quality and accessibility of cameras. Non-ionising imaging techniques, for example, infra-red, are becoming more commensurate with traditional radiographic techniques for caries detection. Nevertheless, X-rays continue to be the leading diagnostic image for dentists, with improved diagnostic potential for lower radiation dose becoming a reality

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

The future of microbiology laboratory classes — wet, dry or in combination?

In recent years, the budgets available for microbiology practical classes have decreased in many university departments in both the United Kingdom and the United States. Although many microbiology educators are wary of the introduction of dry labs, the evidence indicates that, when used in combination with wet labs, dry labs can enhance student learning. In this article, we review the advantages and disadvantages of dry labs compared with wet labs and discuss some of the alternatives available