Background: In this paper, we present the intelligent system to characterize optically human skin; our proposal is a non-invasive way to obtain some parameters of the skin such as the concentration of hemoglobin, water percentages, and thickness of the layers of the skin.
Material And Methods: To achieve the objective of this work, we used an experimental technique called diffuse reflectance spectrophotometry and numerical calculations, such as the Monte Carlo method and the evolutionary algorithm Evonorm.
Results: Five case studies were performed. In the first two cases with the Monte Carlo method, a simulated diffuse reflectance was obtained with proposed parameters in order to compare the parameters obtained by the evolutionary algorithm and the proposed parameters. In the rest of the cases, an experimental diffuse reflectance obtained from volunteers was used.
Conclusions: Numerical modeling was presented to non-invasively detect some parameters of the skin such as hemoglobin concentration, water percentages, and the thickness of the epidermis, dermis, and hypodermis. It was proposed to use evolutionary algorithms for being robust methods for the optimization of complex problems with a reasonable computational cost.
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http://dx.doi.org/10.1111/srt.12866 | DOI Listing |
Cancer Causes Control
January 2025
North Valley Breast Clinic, 1335 Buenaventura Blvd, Suite 204, Redding, CA, 96001, USA.
Objectives: Automated breast ultrasound imaging (ABUS) results in a reduction in breast cancer stage at diagnosis beyond that seen with mammographic screening in women with increased breast density or who are at a high risk of breast cancer. It is unknown if the addition of ABUS to mammography or ABUS imaging alone, in this population, is a cost-effective screening strategy.
Methods: A discrete event simulation (Monte Carlo) model was developed to assess the costs of screening, diagnostic evaluation, biopsy, and breast cancer treatment.
Lifetime Data Anal
January 2025
Institut Camille Jordan, UMR 5208, Université Claude Bernard Lyon 1, Bat. Braconnier, 43, blvd du 11 novembre 1918, F - 69622, Villeurbanne Cedex, France.
Based on the expectile loss function and the adaptive LASSO penalty, the paper proposes and studies the estimation methods for the accelerated failure time (AFT) model. In this approach, we need to estimate the survival function of the censoring variable by the Kaplan-Meier estimator. The AFT model parameters are first estimated by the expectile method and afterwards, when the number of explanatory variables can be large, by the adaptive LASSO expectile method which directly carries out the automatic selection of variables.
View Article and Find Full Text PDFJ Chem Phys
January 2025
Department of Chemistry, Indian Institute of Science Education and Research (IISER) Tirupati, Tirupati, Andhra Pradesh 517619, India.
Although impurities are unavoidable in real-world and experimental systems, most numerical studies on nucleation focus on pure (impurity-free) systems. As a result, the role of impurities in phase transitions remains poorly understood, especially for systems with complex free energy landscapes featuring one or more intermediate metastable phases. In this study, we employed Monte Carlo simulations to investigate the effects of static impurities (quenched disorder) of varying length scales and surface morphologies on the crystal nucleation mechanism and kinetics in the Gaussian core model system-a representative model for soft colloidal systems.
View Article and Find Full Text PDFCPT Pharmacometrics Syst Pharmacol
January 2025
Division of Clinical Pharmacology, Department of Pediatrics, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Sotalol, a class III antiarrhythmic agent, is used to maintain sinus rhythm in patients with atrial fibrillation or atrial flutter (AFIB/AFL). Despite its efficacy, sotalol's use is limited by its potential to cause life-threatening ventricular arrhythmias due to QT interval prolongation. Traditionally, sotalol administration required hospitalization to monitor these risks.
View Article and Find Full Text PDFGenet Epidemiol
January 2025
Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
In large cohort studies the number of unaffected individuals outnumbers the number of affected individuals, and the power can be low to detect associations for outcomes with low prevalence. We consider how including recorded family history in regression models increases the power to detect associations between genetic variants and disease risk. We show theoretically and using Monte-Carlo simulations that including a family history of the disease, with a weighting of 0.
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