A two-tier optimization strategy for feature selection in robust adversarial attack mitigation on internet of things network security by Kashi Sai Prasad, P Udayakumar, E. Laxmi Lydia, Mohammed Altaf Ahmed, Mohamad Khairi Ishak, Faten Khalid Karim, Samih M. Mostafa

“…Numerous research works were keen to project intelligent network intrusion detection systems (NIDS) to avert the exploitation of IoT data through smart applications. Deep learning (DL) models are applied to perceive and alleviate numerous security attacks against IoT networks. …”
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Empowering Security Operation Center With Artificial Intelligence and Machine Learning—A Systematic Literature Review by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…Various methods, ranging from automated incident response and behavioral analytics to neural networks and deep learning, have been classified and compared. In addition, an in-depth reference architectural model, which is a blueprint for SOC integrating AI and ML into SOCs, is introduced. …”
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Preparing physiotherapists for the future: the development and evaluation of an innovative curriculum by Niki Stolwijk, Anne van Bergen, Evy Jetten, Marjo Maas

“…Areas for improvement were self-directed learning support, and teaching strategies to prompt deep learning. Conclusion The evaluation showed that the guiding principles of PACE were implemented as intended and that the innovation positively contributed to student learning,…”
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A Semi-Supervised Attention Model for Identifying Authentic Sneakers by Yang Yang, Nengjun Zhu, Yifeng Wu, Jian Cao, Dechuan Zhan, Hui Xiong

“…The advancement of deep learning techniques for fine-grained object recognition creates new possibilities for genuine product identification. …”
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Predicting the exposure of mycophenolic acid in children with autoimmune diseases using a limited sampling strategy: A retrospective study by Ping Zheng, Ting Pan, Ya Gao, Juan Chen, Liren Li, Yan Chen, Dandan Fang, Xuechun Li, Fei Gao, Yilei Li

“…This study aims to use machine learning and deep learning algorithms to develop a prediction model of MPA exposure for pediatric autoimmune diseases with optimizing sampling frequency. …”
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Prospective de novo drug design with deep interactome learning by Kenneth Atz, Leandro Cotos, Clemens Isert, Maria Håkansson, Dorota Focht, Mattis Hilleke, David F. Nippa, Michael Iff, Jann Ledergerber, Carl C. G. Schiebroek, Valentina Romeo, Jan A. Hiss, Daniel Merk, Petra Schneider, Bernd Kuhn, Uwe Grether, Gisbert Schneider

“…We present a computational approach utilizing interactome-based deep learning for ligand- and structure-based generation of drug-like molecules. …”
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The Application of an Intelligent <i>Agaricus bisporus</i>-Harvesting Device Based on FES-YOLOv5s by Hao Ma, Yulong Ding, Hongwei Cui, Jiangtao Ji, Xin Jin, Tianhang Ding, Jiaoling Wang

“…This device mainly comprised a frame, camera, truss-type robotic arm, flexible manipulator, and control system. The FES-YOLOv5s deep learning target detection model was used to accurately identify and locate <i>Agaricus bisporus</i>. …”
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Machine Learning in the Management of Patients Undergoing Catheter Ablation for Atrial Fibrillation: Scoping Review by Aijing Luo, Wei Chen, Hongtao Zhu, Wenzhao Xie, Xi Chen, Zhenjiang Liu, Zirui Xin

“…In terms of model type, deep learning, represented by convolutional neural networks, was most frequently applied (14/23, 61%). …”
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Dual-stream disentangled model for microvascular extraction in five datasets from multiple OCTA instruments by Xiaoyang Hu, Xiaoyang Hu, Jinkui Hao, Quanyong Yi, Yitian Zhao, Jiong Zhang

“…However, noise and artifacts from different imaging instruments can interfere with segmentation, and most existing deep learning models struggle with segmenting small vessels and capturing low-dimensional structural information. …”
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Exploring the application of knowledge transfer to sports video data by Shahrokh Heidari, Gibran Zazueta, Riki Mitchell, David Arturo Soriano Valdez, Mitchell Rogers, Mitchell Rogers, Jiaxuan Wang, Ruigeng Wang, Marcel Noronha, Alfonso Gastelum Strozzi, Mengjie Zhang, Patrice Jean Delmas, Patrice Jean Delmas

“…A major limitation of training deep learning models on large datasets is the significant resource requirement for reproducing results. …”
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Early Detection of Multiwavelength Blazar Variability by Hermann Stolte, Jonas Sinapius, Iftach Sadeh, Elisa Pueschel, Matthias Weidlich, David Berge

“…For this purpose, we have developed a novel deep learning analysis framework, based on data-driven anomaly detection techniques. …”
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A Survey on Reconfigurable Intelligent Surface for Physical Layer Security of Next-Generation Wireless Communications by Ravneet Kaur, Bajrang Bansal, Sudhan Majhi, Sandesh Jain, Chongwen Huang, Chau Yuen

“…For multiple-input single-output (MISO) case, PLS strategies such as inducing artificial noise (AN), optimization algorithms, alternating optimization (AO), machine learning (ML) and deep learning (DL), and reflect matrices are discussed. …”
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LipBengal: Pioneering Bengali lip-reading dataset for pronunciation mapping through lip gesturesHugging Face by Md. Tanvir Rahman Sahed, Md. Tanjil Islam Aronno, Hussain Nyeem, Md. Abdul Wahed, Tashrif Ahsan, R Rafiul Islam, Tareque Bashar Ovi, Manab Kumar Kundu, Jane Alam Sadeef

“…Captured under diverse and uncontrolled conditions, LipBengal stands as the most extensive Bengali lip-reading dataset to date, designed to facilitate robust benchmarking and validation of novel deep learning architectures. Detailed annotations extend from phoneme- level classifications to full sentence constructions, providing a granular and comprehensive dataset. …”
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SFMHANet: Surface Fitting Constrained Multidimensional Hybrid Attention Network for Aero-Optics Thermal Radiation Effect Correction by Yu Shi, ShanLin Niu, Lei Wang, Liang Ye, YaoZong Zhang, HanYu Hong

“…In order to handle multiple types of aero-optics thermal radiation effects effectively and to combine the advantages of image prior constraints and deep learning networks, we propose a surface fitting constrained multidimensional hybrid attention aero-optics thermal radiation correction network (SFMHANet) in this article. …”
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Automated on-site broiler live weight estimation through YOLO-based segmentation by Mahmoud Y. Shams, Wael M. Elmessery, Awad Ali Tayoush Oraiath, Ahmed Elbeltagi, Ali Salem, Pankaj Kumar, Tamer M. El-Messery, Tarek Abd El-Hafeez, Mohamed F. Abdelshafie, Gomaa G. Abd El-Wahhab, Ibrahim S. El-Soaly, Abdallah Elshawadfy Elwakeel

“…The study utilizes YOLO version 8, a deep learning-based network segmentation technique, for precise broiler segmentation, significantly improving weight accuracy in complex environments. …”
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An underground coal mine multi-target detection algorithm by FAN Shoujun, CHEN Xilin, WEI Liangyue, WANG Qingyu, ZHANG Shiyuan, DONG Fei, LEI Shaohua

“…Currently, underground coal mine target detection algorithms based on deep learning show poor performance in detecting complex small targets under conditions of uneven light intensity distribution, complex target environments, and imbalanced multi-class target scale distribution, often resulting in missed detection and false detection. …”
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Using partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images by Yida Wang, Ankang Gao, Hongxi Yang, Jie Bai, Guohua Zhao, Huiting Zhang, Yang Song, Chenglong Wang, Yong Zhang, Jingliang Cheng, Guang Yang

“…Region of interests comprising the entire tumor and peritumoral edema were automatically segmented using a pre-trained deep learning model. Radiomic features were extracted from T1-weighted, T2-weighted, post-Gadolinium T1 weighted, and T2 fluid-attenuated inversion recovery images. …”
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Informatics strategies for early detection and risk mitigation in pancreatic cancer patients by Di Jin, Najeeb Ullah Khan, Wei Gu, Huijun Lei, Ajay Goel, Tianhui Chen

“…AI-driven approaches, such as those employed in Project Felix and CancerSEEK, have been highlighted for their potential to enhance early detection through deep learning and biomarker discovery. This review underscores the importance of universal genetic testing and the integration of AI with traditional diagnostic methods to improve outcomes in high-risk individuals. …”
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Investigating Maps of Science Using Contextual Proximity of Citations Based on Deep Contextualized Word Representation by Muhammad Roman, Abdul Shahid, Shafiullah Khan, Lisu Yu, Muhammad Asif, Yazeed Yasin Ghadi

“…For automated classification, we need to train deep learning models, which take the citation context as input and provides the reason for citing a paper. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…Conclusion We have innovatively established a deep learning-based prediction model, DCRGS, for the prediction of the prognosis of patients with LUAD. …”
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