Machine Learning-Enhanced Discrimination of Gamma-Ray and Hadron Events Using Temporal Features: An ASTRI Mini-Array Analysis by Valentina La Parola, Giancarlo Cusumano, Saverio Lombardi, Antonio Alessio Compagnino, Antonino La Barbera, Antonio Tutone, Antonio Pagliaro

“…Our methodology employs a Random Forest classifier with optimized hyperparameters, trained on a balanced dataset of gamma and hadron events. …”
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Finding a suitable chest x-ray image size for the process of Machine learning to build a model for predicting Pneumonia by Kriengsak Yothapakdee, Yosawaj Pugtao, Sarawoot Charoenkhun, Tanunchai Boonnuk, Kreangsak Tamee

“…This study focused on algorithm performance and training/testing time, evaluating the most suitable chest X-ray image size for machine learning models to predict pneumonia infection. …”
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Employment of a Radial Basis Function Model for Predicting the Heating Load of Construction by Yuxuan Dai

“…The innovative approaches presented in this research consist of integrating 2 advanced optimizers, namely an Improved Manta-Ray Foraging Optimizer (IMRFO) and a Population-based Vortex Search Algorithm (PVSA), with a Radial Basis Function (RBF). …”
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YOLO-TARC: YOLOv10 with Token Attention and Residual Convolution for Small Void Detection in Root Canal X-Ray Images by Yin Pan, Zhenpeng Zhang, Xueyang Zhang, Zhi Zeng, Yibin Tian

“…By tokenizing feature maps and enhancing local focusing, it enables the model to pay closer attention to small targets. Additionally, to optimize the training process, a bounding box loss function is adopted to achieve faster and more accurate bounding box predictions. …”
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FLPneXAINet: Federated deep learning and explainable AI for improved pneumonia prediction utilizing GAN-augmented chest X-ray data. by Shuvo Biswas, Rafid Mostafiz, Mohammad Shorif Uddin, Muhammad Shahin Uddin

“…The dataset was preprocessed and augmented using a cycle-consistent generative adversarial (CycleGAN) network to increase the volume of training data. Three pre-trained DL models named VGG16, NASNetMobile, and MobileNet were employed to extract features from the augmented dataset. …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

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Single Photon Emission Computed Tomography/X-ray Computed Tomography-based radiomics analysis for diagnosis of bone metastases in patients with breast cancer by Huiyu Su, Chunwen Ma, Dongli Sun, Jianhua Jin

“…This study intended to investigate the efficacy of Single Photon Emission Computed Tomography/X-ray Computed Tomography (SPECT/CT) in diagnosing bone metastases in BC and to develop a model for predicting the diagnostic effectiveness. …”
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Bone Age Estimation of Chinese Han Adolescents’s and Children’s Elbow Joint X-rays Based on Multiple Deep Convolutional Neural Network Models by LI Dan-yang, ZHOU Hui-ming, WAN Lei, LIU Tai-ang, LI Yuan-zhe, WANG Mao-wen, WANG Ya-hui

“…The DenseNet121 model with Scheme 3 achieves optimal performance. Using segmentation networks, especially that trained with annotation areas encompassing the full elbow joint including the distal humerus, proximal radius, and proximal ulna, can improve the accuracy of bone age estimation based on elbow joint X-ray images.…”
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AI-based X-ray fracture analysis of the distal radius: accuracy between representative classification, detection and segmentation deep learning models for clinical practice by Marco Reisert, Fabian Bamberg, Maximilian Frederik Russe, Philipp Rebmann, Phuong Hien Tran, Elias Kellner, Elmar Kotter, Suam Kim

“…Representative classification and segmentation models were trained on 80% of the data. After output binarisation, their derived fracture detection performances as well as that of a standard commercially available solution were compared on the remaining X-rays (20%) using mainly accuracy and area under the receiver operating characteristic (AUROC).Results A total of 2856 examinations with 712 (24.9%) fractures were included in the analysis. …”
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Enhancing Fracture Detection in Remote Settings: Evaluating the Efficacy of FIXUS AI Deep Learning Algorithms in Identifying Fifth Metatarsal Fractures Using Mixed-Quality X-rays by Atta Taseh MD, Alireza Gholipour PhD, Mani Eftekhari, Alireza Ebrahimi MD, Alexandra F. Flaherty MD, MS, Alexandra F. Flaherty MD, MS, Sumner Jones, Varun Nukala, Gregory R. Waryasz MD, Daniel Guss MD, MBA, John Y. Kwon MD, Christopher W. DiGiovanni MD, Lorena Bejarano-Pineda MD, Soheil Ashkani-Esfahani MD

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Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches by Suleiman Ibrahim Mohammad, Hamza Abu Owida, Asokan Vasudevan, Suhas Ballal, Shaker Al-Hasnaawei, Subhashree Ray, Naveen Chandra Talniya, Aashna Sinha, Vatsal Jain, Ahmad Abumalek

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Aerobic VS Anaerobic Exercise on Body Composition and Hormonal Adaptations in Athletes and Non-Athletes: A Randomized Controlled Trial by Md Shahariar Kabir, Sunita Yadav, Subhashis Biswas, Sangeeta Pradhan, Vlad Adrian Geantă

“…Background:This study examined the differential effects of aerobic and anaerobicexercise on body composition and hormonal adaptations in athletes and non-athletes, providing evidence-based recommendations for optimizing fitness andhealth outcomes, such as training duration, frequency, and the combination ofaerobic and anaerobic exercises. …”
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Detection of single and dual pulmonary diseases using an optimized vision transformer by Almughamisi Naif, Abosamra Gibrael, Albar Adnan, Saleh Mostafa

“…This study aimed to adapt and optimize the pre-trained ViT-B16 model to predict and distinguish between single and dual pulmonary diseases whose diagnoses relied only on CXRs. …”
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Diagnostic Performance of Artificial Intelligence in Chest Radiographs Referred from the Emergency Department by Julia López Alcolea, Ana Fernández Alfonso, Raquel Cano Alonso, Ana Álvarez Vázquez, Alejandro Díaz Moreno, David García Castellanos, Lucía Sanabria Greciano, Chawar Hayoun, Manuel Recio Rodríguez, Cristina Andreu Vázquez, Israel John Thuissard Vasallo, Vicente Martínez de Vega

“…Background: The increasing integration of AI in chest X-ray evaluation holds promise for enhancing diagnostic accuracy and optimizing clinical workflows. …”
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Effect of whole-body vibration training on bone mineral density in older adults: a systematic review and meta-analysis by Danilo A. Massini, Tiago A. F. Almeida, Anderson G. Macedo, André B. Peres, Víctor Hernández-Beltrán, José M. Gamonales, Mário C. Espada, Cassiano M. Neiva, Dalton M. Pessôa Filho

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CT radiomics from intratumor and peritumor regions for predicting poorly differentiated invasive nonmucinous pulmonary adenocarcinoma by Lijun Duan, Wenyun Liu, Mingyang Li, Liang Guo, Mengran Ren, Xin Dong, Xiaoqian Lu, Dianbo Cao

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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…The X-ray defect detection system for weld seams in deep-sea manned spherical shells is nonlinear and complex, posing challenges such as motor parameter variations, external disturbances, coupling effects, and high-precision dual-motor coordination requirements. …”
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Wide-angle deep ultraviolet antireflective multilayers via discrete-to-continuous optimization by Kim Jae-Hyun, Kim Dong In, Lee Sun Sook, An Ki-Seok, Yim Soonmin, Lee Eungkyu, Kim Sun-Kyung

“…Good training datasets facilitate the optimization process, particularly when an objective function has a non-convex shape containing multiple local optima in a continuous parametric space. …”
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Optimizing radiography education: Adapting curricula to evolving clinical practices in UAE healthcare by Mohammad Rawashdeh, Mohamed Zakaria El-Sayed, Labeeba Hussain, Siddra Asadullah, Arshad Ahammed Sharaf, Mohamed M. El Safwany, Mark McEntee, Andrew Englend, Magdi A. Ali

“…Background: Despite population growth, the UAE is experiencing a decline in the utilization of plain radiography (X-ray) due to changes in clinical priorities and advancements in imaging technologies like CT and MRI. …”
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Determination of Radiation Dose Rate in Radiology Installations Using Raysafe X2 Surveymeter by Susi Andriati, Feriska Handayani Irka, Nini Firmawati, Ade Wahyuni, Ramacos Fardela

“…The relatively low dose rates in the conventional X-ray and mammography rooms suggest effective radiation shielding and adherence to safety protocols. …”
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