Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques.

Machine learning offers significant potential for lung cancer detection, enabling early diagnosis and potentially improving patient outcomes. Feature extraction remains a crucial challenge in this domain. Combining the most relevant features can further enhance detection accuracy. This study employed a hybrid feature extraction approach, which integrates both Gray-level co-occurrence matrix (GLCM) with Haralick and autoencoder features with an autoencoder. These features were subsequently fed into supervised machine learning methods. Support Vector Machine (SVM) Radial Base Function (RBF) and SVM Gaussian achieved perfect performance measures, while SVM polynomial produced an accuracy of 99.89% when utilizing GLCM with an autoencoder, Haralick, and autoencoder features. SVM Gaussian achieved an accuracy of 99.56%, while SVM RBF achieved an accuracy of 99.35% when utilizing GLCM with Haralick features. These results demonstrate the potential of the proposed approach for developing improved diagnostic and prognostic lung cancer treatment planning and decision-making systems.

A Numerical Investigation on Hydrothermal Performance of Micro Channel Heat Sink with Periodic Spatial Modification on Sidewalls.

Electronic gadgets have been designed to incorporating very small components such as microcontrollers, electronic chips, transistors, microprocessors, etc. These components are exceptionally heat sensitive and can be wrecked if heat is not released. As a result, the thermal control of such components is critical to their optimum performance and extended life. The use of a microchannel heat sink (MCHS) has shown promising solutions to remove the excess heat. In this paper, we have proposed a novel design of MCHS and investigated it numerically. Four different surface modifications on the sidewall of the passage, namely, extended triangular surface (ETS), extended circular surface (ECS), triangular groove surface (TGS), and the circular groove surface (CGS) in the passage of the microchannel have been exploited in the Reynolds number of 100-900. In the presence of geometrical modification, the cooling capacities have been enhanced. The results show that the Nusselt numbers of ETS-MCHS, ECS-MCHS, TGS-MCHS, and CGS-MCHS are increased by 4.30, 3.61, 1.62, and 1.41 times in comparison to the Nusselt number of MCHS with smooth passage, while the friction factor values are increased by 7.33, 6.03, 2.74, and 1.68 times, respectively. In addition, the thermohydraulic performance parameter (THPP) has been evaluated and discussed. The fact that MCHS have THPP values greater than unity demonstrates that the passage's geometries are a practical means of achieving effective thermal management.