Performance and clinical implications of machine learning models for detecting cervical ossification of the posterior longitudinal ligament: a systematic review by Wongthawat Liawrungrueang, Sung Tan Cho, Watcharaporn Cholamjiak, Peem Sarasombath, Nattaphon Twinprai, Prin Twinprai, Inbo Han

“…The ML and DL models demonstrated high diagnostic performance, with accuracy rates ranging from 69.6% to 98.9% and AUC values up to 0.99. Convolutional neural networks and random forest models were the most used approaches. …”
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Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data by Maoyue Zhang

“…At present, most of the research on academic emotions focuses on the concept, current situation, and relevance. …”
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Well logging super-resolution based on fractal interpolation enhanced by BiLSTM-AMPSO by Jian Han, Yu Deng, Bing Zheng, Zhimin Cao

“…In order to address these challenges, geophysical logging is one of the most important data for characterizing target reservoir model. …”
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Flow Field Analysis and Development of a Prediction Model Based on Deep Learning by Yingjie Yu, Xiufeng Zhang, Lucai Wang, Rui Tian, Xiaobin Qian, Dongdong Guo, Yanwei Liu

“…The CNNs–MHA–BiLSTMs model integrates multiple convolutional neural networks (CNNs) in parallel, multi-head attention (MHA), and bidirectional long short-term memory networks (BiLSTMs). …”
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Unraveling trends in schistosomiasis: deep learning insights into national control programs in China by Qing Su, Cici Xi Chen Bauer, Robert Bergquist, Zhiguo Cao, Fenghua Gao, Zhijie Zhang, Yi Hu

“…This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China. …”
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An enhanced deep learning-based feature extraction framework for moving object detection by Upasana Panigrahi, Prabodh Kumar Sahoo, Manoj Kumar Panda, Aswini Kumar Samantaray, Ganapati Panda

“…The developed decoder architecture consists of stacked transposed convolutional layers tasked with translating features back into the image. …”
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Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation by Shan Zhu

“…When building the neural network model, four convolutional layers, two fully connected layers, and one softmax output layer were conceived, and dropout was used to randomly suspend the work of some neurons to avoid overfitting. …”
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FBI-Net: Frequency-Based Image Forgery Localization via Multitask Learning With Self-Attention by A-Rom Gu, Ju-Hyeon Nam, Sang-Chul Lee

“…Our proposed network adopts a fully convolutional encoder-decoder architecture, consisting of three encoders sharing parameters, a bridge attention module, and two output streams in the decoder. …”
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Enhancing Periodontal Bone Loss Diagnosis Through Advanced AI Techniques by Nader Nabil Fouad Rezallah, George Sherif, Ahmed Z. Abdelkarim, Shereen Afifi

“…Based on our extensive research, we concluded that convolutional neural networks (CNNs) are the most effective type of neural network for addressing our problem. …”
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Improving the accuracy of prediction models for small datasets of Cytochrome P450 inhibition with deep learning by Elpri Eka Permadi, Reiko Watanabe, Kenji Mizuguchi

“…This study underscores the significant potential of multitask deep learning, particularly when utilising a graph convolutional network with data imputation, to enhance the accuracy of CYP inhibition predictions under the conditions of limited data availability. …”
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MTFSR: Multitemporal and Spatial Feature Reconstruction Denoising Network for Remote Sensing Change Detection by YeKai Cui, Peng Duan, Jinjiang Li

“…With the widespread application of convolutional neural networks (CNNs) in remote sensing (RS) technologies, change detection (CD) has attracted increasing attention in environmental monitoring research. …”
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Mastitis Classification in Dairy Cows Using Weakly Supervised Representation Learning by Soo-Hyun Cho, Mingyung Lee, Wang-Hee Lee, Seongwon Seo, Dae-Hyun Lee

“…The proposed method employed a structure where the classifier branches from the latent space of a 1D-convolutional autoencoder, enabling representation learning of milking data to be conducted from the perspective of reconstructing the original information and detecting mastitis. …”
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Development of an optimized deep learning model for predicting slope stability in nano silica stabilized soils by Ishwor Thapa, Sufyan Ghani, Prabhu Paramasivam, Mitiku Adare Tufa

“…This study suggests a hybrid classification model of deep learning, integration of convolutional neural networks (CNN), long short-term memory (LSTM), and recurrent neural networks (RNN), optimized by Optuna to predict the stability of NS stabilized infinite slope. …”
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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…For the feature selection process, the binary grey wolf optimization (BGWO) model is employed to identify and retain the most significant features in the dataset. The classification process utilizes ensemble models, including the Temporal Convolutional Network (TCN), the Attention-based Bidirectional Gated Recurrent Unit (A-BiGRU), and the Hybrid Deep Belief Network (HDBN) techniques. …”
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P-68 LIVGUARD, A DEEP NEURAL NETWORK FOR CIRRHOSIS DETECTION IN LIVER ULTRASOUND (USD) IMAGES by DIEGO ARUFE, Pablo Gomez del Campo, Ezequiel Demirdjian, Carlos Galmarini

“…The output of the efficientNetv2 convolutional neural network (CNN) was a score between 0 and 1 to exhibit the probability of cirrhosis. …”
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Modeling and Evaluating the Impact of Mobile Usage on Pedestrian Behavior at Signalized Intersections: A Machine Learning Perspective by Faizanul Haque, Farhan Ahmad Kidwai, Ishwor Thapa, Sufyan Ghani, Lincoln M. Mtapure

“…Advanced machine learning models, including Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Recurrent Neural Networks (RNN), have been applied to analyze and predict MU behavior. …”
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Classification of tomato leaf disease using Transductive Long Short-Term Memory with an attention mechanism by Aarthi Chelladurai, D.P. Manoj Kumar, S. S. Askar, Mohamed Abouhawwash, Mohamed Abouhawwash

“…Tomatoes are considered one of the most valuable vegetables around the world due to their usage and minimal harvesting period. …”
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Predicting the Spread of Vessels in Initial Stage Cervical Cancer through Radiomics Strategy Based on Deep Learning Approach by Piyush Kumar Pareek, Prasath Alais Surendhar S, Ram Prasad, Govindaraj Ramkumar, Ekta Dixit, R. Subbiah, Saleh H. Salmen, Hesham S. Almoallim, S. S. Priya, S. Arockia Jayadhas

“…Novel methods and materials are used in healthcare applications for finding cancer in various parts of the human system. To select the most suitable therapy plan for individuals with domestically progressed cervical cancer, robustness metrics are required to estimate their early phase. …”
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RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection by Zhong Wang, Lanfang Lei, Tong Li, Xian Zu, Peibei Shi

“…First, we designed a high-efficiency hybrid encoder that combines convolutional and Transformer features, thus reducing computational cost while preserving crucial smoke details. …”
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Personalizing Seizure Detection for Individual Patients by Optimal Selection of EEG Signals by Rosanna Ferrara, Martino Giaquinto, Gennaro Percannella, Leonardo Rundo, Alessia Saggese

“…The system uses an efficient Convolutional Neural Network that processes data from just two channels. …”
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