(IoT) Network intrusion detection system using optimization algorithms by Luo Shan

“…In multi-class attack identification scenarios, the framework mitigates feature confusion between rare attacks (e.g., user-to-root attacks) and normal traffic through adaptive feature weight allocation. …”
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Artificial Intelligence for data modeling in triboelectric nanogenerators by Chenjia Li, Ali Matin Nazar

“…Deep learning techniques are shown to enhance noise filtering, feature extraction, and adaptive feedback, transforming TENGs into intelligent platforms for healthcare, robotics, IoT systems, and smart environments. …”
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Enhancing Cybersecurity: Hybrid Deep Learning Approaches to Smishing Attack Detection by Tanjim Mahmud, Md. Alif Hossen Prince, Md. Hasan Ali, Mohammad Shahadat Hossain, Karl Andersson

“…To enhance cybersecurity and address these challenges, this paper proposes a hybrid deep learning approach that combines Bidirectional Gated Recurrent Units (Bi-GRUs) and Convolutional Neural Networks (CNNs), referred to as CNN-Bi-GRU, for the accurate identification and classification of smishing attacks. …”
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A case report of neuronal intranuclear inclusion disease and literature review by Jie Li, Guogao Zhang, Jianrong Zheng, Jun Hu, Yunong Li

“…The identification of GGC-repeat expansions in the Notch 2 N-terminal like C (NOTCH2NLC) gene facilitates the accurate diagnosis of NIID. …”
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Retinal fundus imaging-based diabetic retinopathy classification using transfer learning and fennec fox optimization by Indresh Kumar Gupta, Shruti Patil, Supriya Mahadevkar, Ketan Kotecha, Awanish Kumar Mishra, Joel J.P.C. Rodrigues

“…The proposed FIDRC-DLFFO model automates DR detection and classification by combining median filtering for noise reduction, Inception-ResNet-v2 for feature extraction, and a gated recurrent unit (GRU) for classification. 2. …”
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Deep‐GB: A novel deep learning model for globular protein prediction using CNN‐BiLSTM architecture and enhanced PSSM with trisection strategy by Sonia Zouari, Farman Ali, Atef Masmoudi, Sarah Abu Ghazalah, Wajdi Alghamdi, Faris A. Kateb, Nouf Ibrahim

“…To address the need for precise GP identification, this research introduces an innovative approach that employs a hybrid‐based deep learning model called Deep‐GP. …”
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Recognition of cancer mediating genes using MLP-SDAE model by Sougata Sheet, Ranjan Ghosh, Anupam Ghosh

“…Our model, MLP-SDAE is trained using Stacked Denoising Auto-Encoder for feature selection, and backpropagation is employed within the MLP structure. …”
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The control effect of the pore and fracture characteristics of tectonic coal assisted by the triaxial stress permeability system on permeability by Shi wenfang, Ru zhongliang, Zhao binbin, Lu guoju

“…Furthermore, high-resolution fracture images are collected, and DL-based methods are utilized for fracture identification and feature extraction. Based on these findings, a permeability prediction model is developed to assess the applicability of DL in predicting the permeability of tectonic coal. …”
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KMBARC registry: protocol for a multicentre observational cohort study on non-cystic fibrosis bronchiectasis in Korea by Yun Su Sim, Hyun Lee, Hayoung Choi, Shinhee Park, Woo Jin Kim, Kwang Ha Yoo, Seung Jun Lee, Tae-Hyung Kim, Bumhee Yang, Ina Jeong, Soo-Jung Um, Deog Kyeom Kim, Ji-Hyun Lee, Byoung Soo Kwon, Young-Jae Cho, Hye Yun Park, Chin Kook Rhee, Sang Haak Lee, Ju Ock Na, An-Soo Jang, Ji Ye Jung, Seung Won Ra, Ji-Ho Lee, Sang-Ha Kim, Changhwan Kim, Youlim Kim, Chang Youl Lee, Hyun Kuk Kim, Jae Seung Lee, Sei Won Lee, Yeon-Mok Oh

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A hybrid model for detecting motion artifacts in ballistocardiogram signals by Yuelong Jiang, Han Zhang, Qizheng Zeng

“…Employing a dual-channel approach, the model integrates multi-scale feature judgment with a BiGRU–FCN deep learning model. …”
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