RESUMEN
Identifying colour from a distance is challenging due to the external noise associated with the measurement process. The present study focuses on developing a colour measuring system and a novel Multi-target Regression (MTR) model for accurate colour measurement from distance. Herein, a novel MTR method, referred as Multi-Objective Stacked Regression (MOSR) is proposed. The core idea behind MOSR is based on stacking as an ensemble approach with multi-objective evolutionary learning using NSGA-II. A multi-objective optimization approach is used for selecting base learners that maximises prediction accuracy while minimising ensemble complexity, which is further compared with six state-of-the-art methods over the colour dataset. Classification and regression tree (CART), Random Forest (RF) and Support Vector Machine (SVM) were used as regressor algorithms. MOSR outperformed all compared methods with the highest coefficient of determination values for all three targets of the colour dataset. Rigorous comparison with state-of-the-art methods over 18 benchmarked datasets showed MOSR outperformed in 15 datasets when CART was used as a regressor algorithm and 11 datasets when RF and SVM were used as regressor algorithms. The MOSR method was statistically superior to compared methods and can be effectively used to measure accurate colour values in the distance-based colour measuring device.
RESUMEN
Background: The COVID-19 pandemic intensified the use of scarce resources, including extracorporeal membrane oxygenation (ECMO) and mechanical ventilation (MV). The combinatorial features of the immune system may be considered to estimate such needs and facilitate continuous open-ended knowledge discovery. Materials and methods: Computer-generated distinct data patterns derived from 283 white blood cell counts collected within five days after hospitalization from 97 COVID-19 patients were used to predict patient's use of hospital resources. Results: Alone, data on separate cell types-such as neutrophils-did not identify patients that required MV/ECMO. However, when structured as multicellular indicators, distinct data patterns displayed by such markers separated patients later needing or not needing MV/ECMO. Patients that eventually required MV/ECMO also revealed increased percentages of neutrophils and decreased percentages of lymphocytes on admission. Discussion/conclusion: Future use of limited hospital resources may be predicted when combinations of available blood leukocyte-related data are analyzed. New methods could also identify, upon admission, a subset of COVID-19 patients that reveal inflammation. Presented by individuals not previously exposed to MV/ECMO, this inflammation differs from the well-described inflammation induced after exposure to such resources. If shown to be reproducible in other clinical syndromes and populations, it is suggested that the analysis of immunological combinations may inform more and/or uncover novel information even in the absence of pre-established questions.
RESUMEN
Periodic fever in children is an autoinflammatory illness with an unknown cause. Symptoms include frequent episodes of fever that are followed by an increase in inflammatory markers. A genetic background for periodic fever of unknown origin has been hypothesized, based on its family clustering and parallels to other autoinflammatory illnesses such as familial Mediterranean fever. Genome analysis has been used in studies to look for related gene variations in periodic fever of unknown origin in the pediatric population. Children with periodic fevers might be a diagnostic challenge. After ruling out the most prevalent causes, a wide variety of other possibilities are investigated. Infectious and noninfectious causes of periodic fever in children are discussed in this article. Inflammasomes (intracellular proteins that activate interleukin (IL)-1b and IL-18) and genetic/hereditary variations are thought to be implicated in the pathogenesis of periodic fever. Evaluation and ruling out possible infective or noninfective causes is vital in the diagnosis of periodic fever in children. Investigations demonstrate that there isn't a single gene linked to it, suggesting that it may have a multifactorial or polygenic origin, with an environmental trigger causing inflammasome activation and fever flares. Treatment is usually symptomatic, with drugs such as colchicine and cimetidine having shown promising results in trials. We explored the literature on periodic fever in children for its epidemiology, pathophysiology, the role of various genes and how they influence the disease and associated complications, and its various treatment modalities.
