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Linked Comment:M.D. Moncrieff and J.P. Nobes. Br J Dermatol 2021; 185:877. Plain language summary available online [ABSTRACT FROM AUTHOR]

Plain language summary available online [ABSTRACT FROM AUTHOR]

During the COVID-19 Pandemic, the need for rapid and reliable alternative COVID-19 screening methods have motivated the development of learning networks to screen COVID-19 patients based on chest radiography obtained from Chest X-ray (CXR) and Computed Tomography (CT) imaging. Although the effectiveness of developed models have been documented, their adoption in assisting radiologists suffers mainly due to the failure to implement or present any applicable framework. Therefore in this paper, a robotic framework is proposed to aid radiologists in COVID-19 patient screening. Specifically, Transfer learning is employed to first develop two well-known learning networks (GoogleNet and SqueezeNet) to classify positive and negative COVID-19 patients based on chest radiography obtained from Chest X-Ray (CXR) and CT imaging collected from three publicly available repositories. A test accuracy of 90.90%, sensitivity and specificity of 94.70% and 87.20% were obtained respectively for SqueezeNet and a test accuracy of 96.40%, sensitivity and specificity of 95.50% and 97.40% were obtained respectively for GoogleNet. Consequently, to demonstrate the clinical usability of the model, it is deployed on the Softbank NAO-V6 humanoid robot which is a social robot to serve as an assistive platform for radiologists. The strategy is an end-to-end explainable sorting of X-ray images, particularly for COVID-19 patients. Laboratory-based implementation of the overall framework demonstrates the effectiveness of the proposed platform in aiding radiologists in COVID-19 screening.

In power systems, optimal power flow (OPF) is a complex and constrained optimization problem in which quite often multiple and conflicting objectives are required to be optimized. The traditional way of dealing with multi-objective OPF (MOOPF) is the weighted sum method which converts the multi-objective OPF into a single-objective problem and provides a single solution from the set of Pareto solutions. This paper presents MOOPF study applying multi-objective evolutionary algorithm based on decomposition (MOEA/D) where a set of non-dominated solutions (Pareto solutions) can be obtained in a single run of the algorithm. OPF is formulated with two or more objectives among fuel (generation) cost, emission, power loss and voltage deviation. The other important aspect in OPF problem is about satisfying power system constraints. As the search process adopted by evolutionary algorithms is unconstrained, for a constrained optimization problem like OPF, static penalty function approach has been extensively employed to discard infeasible solutions. This approach requires selection of a suitable penalty coefficient, largely done by trial-and-error, and an improper selection may often lead to violation of system constraints. In this paper, an effective constraint handling method, superiority of feasible solutions (SF), is used in conjunction with MOEA/D to handle network constraints in MOOPF study. The algorithm MOEA/D-SF is applied to standard IEEE 30-bus and IEEE 57-bus test systems. Simulation results are analyzed, especially for constraint violation and compared with recently reported results on OPF. [ABSTRACT FROM AUTHOR]

The article offers guidelines for topical photodynamic therapy (PDT) released by the British Association of Dermatologists and British Photodermatology Group. It offers overview of the purpose and scope of the guideline aimed at providing updated evidence-based recommendations for use of PDT. It also notes that the recommendation was developed for implementation in the National Health Service in Great Britain.

Summary: Background: Topical photodynamic therapy (PDT) is widely used to treat superficial nonmelanoma skin cancer and dysplasia, and is generally well tolerated. However, as with all treatments, adverse effects may occur and awareness may facilitate approaches to prevention and management. Objectives: To review the available evidence relating to the adverse effects of topical PDT, to help inform recommendations in updated clinical guidelines produced by the British Association of Dermatologists and British Photodermatology Group, and the efficacy of preventative and therapeutic approaches. Methods: This review summarizes the published evidence related to the adverse effects of topical PDT and attempts to interpret this evidence in the context of patient risk and management. Results: Pain and discomfort during PDT are acute adverse effects, which can be minimized through the use of modified and low‐irradiance PDT regimens and do not therefore usually limit successful treatment delivery. Other adverse effects include the risk of contact allergy to photosensitizer prodrugs, although this is rare but should be kept in mind, particularly for patients who have received multiple PDT treatments to larger areas. There are no other significant documented longer‐term risks and, to date, no evidence of cumulative toxicity or photocarcinogenic risk. Conclusions: Topical PDT is usually well tolerated, reinforcing the utility of this important therapeutic option in dermatology practice. The main acute adverse effect of pain can typically be minimized through preventative approaches of modified PDT regimens. Other adverse effects are uncommon and generally do not limit treatment delivery. What's already known about this topic? Photodynamic therapy (PDT) is widely used in dermatology.Pain is the most well documented adverse effect.Methods of effective pain relief are limited. What does this study add? This review scrutinizes the literature relating to adverse effects of PDT and management approaches.PDT‐induced pain can usually be effectively prevented and managed through adjustments to PDT regimens, such as using lower irradiance light delivery.Phototoxic reactions are to be expected.Other adverse effects are typically uncommon and not limiting. Linked Editorial:Wulf. Br J Dermatol 2019; 180:695–696. Plain language summary available online [ABSTRACT FROM AUTHOR]