Achieving Faster and Smarter Chest X-Ray Classification With Optimized CNNs by Hassen Louati, Ali Louati, Khalid Mansour, Elham Kariri

“…However, building accurate and efficient deep learning models for X-ray image classification remains challenging, requiring both optimized architectures and low computational complexity. …”
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Optimized deep learning model for diagnosing tonsil and adenoid hypertrophy through X-rays by Zhiqing Wu, Ran Zhuo, Yali Yang, Xiaobo Liu, Bin Wu, Jian Wang

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Utilizing deep belief network optimized by balanced Manta ray foraging optimization algorithm for estimating the shear Wall’s shear strength by Feng Liu, Zhigui Dong, Bizhan Gorbani

“…This study proposes a model using a Deep Belief Network (DBN) optimized by the Balanced Manta Ray Foraging Optimization Algorithm (BMRFOA) to predict the shear strength of these walls. …”
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Performing Chest X-Rays at Inspiration in Uncooperative Children: The Effect of Exercises with a Training Program for Radiology Technicians by Heinz-Jakob Langen, Christiane Kohlhauser-Vollmuth, Corinna Sengenberger, Johann Bielmeier, Renate Jocher, Martina Eschmann

“…It is difficult to acquire a chest X-ray of a crying infant at maximum inspiration. A computer program was developed for technician training. …”
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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network by Amit Kumar Rai, Nirupama Mandal, Krishna Kant Singh, Ivan Izonin

“…Thus, in this paper, a Radial Basis Function Neural Network (RBFNN) trained using Manta Ray Foraging Optimization algorithm (MRFO) is proposed. …”
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Classification of CT scan and X-ray dataset based on deep learning and particle swarm optimization. by Honghua Liu, Mingwei Zhao, Chang She, Han Peng, Mailan Liu, Bo Li

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Comparison of Deep Learning Models and Optimization Algorithms in the Detection of Scoliosis and Spondylolisthesis from X-Ray Images by Abdullah Erhan Akkaya, Cengiz Hark, Harun Güneş

“…According to the classification processes, the deep learning model with the highest accuracy value was Alexnet, and the optimization algorithm used with it, Sgdm (99.01%), and the training time lasted 38 seconds. …”
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BO-CLAHE enhancing neonatal chest X-ray image quality for improved lesion classification by Jiwon Han, Byungmin Choi, Jae Young Kim, Yeonjoon Lee

“…To address this issue, we propose a method called Bayesian Optimization CLAHE(BO-CLAHE), which leverages Bayesian optimization to automatically select the optimal hyperparameters for X-ray images used in diagnosing lung diseases in preterm and high-risk neonates. …”
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Dietary Protein Intake and Its Associations With Bone Properties Using Peripheral Quantitative Computed Tomography and Dual-Energy X-Ray Absorptiometry in Endurance-Trained Individ... by Silar Gardy, Ada Sevinc, Jennifer Levee, Sofia V Ferreira, Julia-Rose Linardatos, Andrea R Josse, Tyler A Churchward-Venne, Jenna C Gibbs

“…Background: Endurance athletes are at greater risk of compromised bone health due to elevated nutritional demands and high-volume training. Optimal nutritional intake is fundamental to support athlete bone health, and dietary protein is an essential nutrient for the maintenance of bone and muscle tissue. …”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

“…Data Preprocessing was conducted to enhance image quality and extract relevant features, followed by implementing a deep convolutional neural networks (DCNNs) model using TensorFlow’s Keras. Using pre-trained models such as Resnet, transfer learning techniques were employed to learn efficient features from large-scale datasets and optimize the model’s performance with the limited medical data available. …”
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Classification of chest radiographs into healthy/pneumonia using Harris-Hawks Algorithm optimized deep-features by K. Vijayakumar, Mohammad Nazmul Hasan Maziz, Swaetha Ramadasan, Seifedine Kadry, S. Arunmozhi

“…Recently, several pre-trained deep-learning (PDL) based systems are developed to identify disease in different imaging modalities, including the chest X-ray. …”
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Generalizable Solar Irradiance Prediction for Battery Operation Optimization in IoT-Based Microgrid Environments by Ray Colucci, Imad Mahgoub

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ZooCNN: A Zero-Order Optimized Convolutional Neural Network for Pneumonia Classification Using Chest Radiographs by Saravana Kumar Ganesan, Parthasarathy Velusamy, Santhosh Rajendran, Ranjithkumar Sakthivel, Manikandan Bose, Baskaran Stephen Inbaraj

“…Pneumonia, a leading cause of mortality in children under five, is usually diagnosed through chest X-ray (CXR) images due to its efficiency and cost-effectiveness. …”
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End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment by Cong Wang, Valerio Mariani, Frédéric Poitevin, Matthew Avaylon, Jana Thayer

“…X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. …”
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Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography by Arpitha Ravi, Philipp Bernhardt, Mathis Hoffmann, Florian Kordon, Siming Bayer, Stephan Achenbach, Andreas Maier

“…Abstract Optimal selection of X-ray imaging parameters is crucial in coronary angiography and structural cardiac procedures to ensure optimal image quality and minimize radiation exposure. …”
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Stochastic-based learning for image classification in chest X-ray diagnosis by Xinghui Zeng, Shushu Gong

“…The training process utilized stochastic deep learning using stochastic gradient descent, with K-Fold cross-validation and early stopping used for exhaustive model optimization and against overfitting. …”
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Comparative Study of Gamma- Ray Shielding Parameters for Different Epoxy Composites by Amal A. El- Sawy, Eman Sarwat

“… In the current work various types of epoxy composites were added to concrete to enhance its effectiveness as a gamma- ray shield. Four epoxy samples of (E/clay/B4C) S1, (E/Mag/B4C) S2, (EPIL) S3 and (Ep) S4 were used in a comparative study of gamma radiation attenuation properties of these shields that calculating using Mont Carlo code (MCNP-5). …”
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Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images by Resky Adhyaksa, Bedy Purnama

“…This architecture consists of five blocks of convolutional and max-pooling layers to effectively extract and enhance information from the images for precise classification. The training and testing phases utilized an 80:20 split of the data, employing binary cross-entropy as the loss function and the Adam optimizer for efficient weight updates. …”
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Denoising diffusion probabilistic models for addressing data limitations in chest X-ray classification by Evi M.C. Huijben, Josien P.W. Pluim, Maureen A.J.M. van Eijnatten

“…This study explores the potential of a DDPM to generate synthetic chest X-rays for multi-label classifier training. The results indicate that the use of a conditional DDPM has the potential to produce a realistic training set of synthetic chest X-rays. …”
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Beyond Traditional Biometrics: Harnessing Chest X-Ray Features for Robust Person Identification by Farah Hazem, Bennour Akram, Tahar Mekhaznia, Fahad Ghabban, Abdullah Alsaeedi, Bhawna Goyal

“…Person identification through chest X-ray radiographs stands as a vanguard in both healthcare and biometrical security domains. …”
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