Multi-view mixture-of-experts for predicting molecular properties using SMILES, SELFIES, and graph-based representations by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Indra Priyadarsini, Seiji Takeda

“…With the increasing demand for training efficiency, mixture-of-experts (MoEs) has become essential for scaling large models by selectively activating sub-networks of experts through a gating network, thereby optimizing performance. …”
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Statistical modelling and forecasting of HIV and anti-retroviral therapy cases by time-series and machine learning models by Abdullah M. Almarashi

“…Various time series models including ARIMA (Auto-regressive integrated moving average), exponential smoothing (Brown, Holt, Winter), neural network auto-regressive model (NNAR), and ETS (Exponential Smoothing State space) models were applied to analyze and forecast the monthly patterns of HIV and ART cases. …”
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NoctuDroneNet: Real-Time Semantic Segmentation of Nighttime UAV Imagery in Complex Environments by Ruokun Qu, Jintao Tan, Yelu Liu, Chenglong Li, Hui Jiang

“…In this paper, we introduce NoctuDroneNet (Nocturnal UAV Drone Network, hereinafter referred to as NoctuDroneNet), a real-time segmentation model tailored specifically for nighttime UAV scenarios. …”
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Comprehensive Performance Comparison of Signal Processing Features in Machine Learning Classification of Alcohol Intoxication on Small Gait Datasets by Muxi Qi, Samuel Chibuoyim Uche, Emmanuel Agu

“…Recent research has explored machine learning-based approaches using smartphone accelerometers to classify intoxicated gait patterns. While neural network approaches have emerged, due to the significant challenges with collecting intoxicated gait data, gait datasets are often too small to utilize such approaches. …”
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Immune-associated molecular classification and prognosis signature of sepsis. by Zhiwei Li, Leyi Wang, Shuting Yang, Bin Luo, Yezi Liu, Mengsi Chen, Changmin Wang

“…An unsupervised cluster analysis was used to identify potential molecular subtypes of sepsis, and a weighted gene co-expression network analysis was performed to identify gene modules. …”
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Causal relationships and predictability of the summer East Atlantic teleconnection by J. Carvalho-Oliveira, J. Carvalho-Oliveira, J. Carvalho-Oliveira, J. Carvalho-Oliveira, G. Di Capua, G. Di Capua, L. F. Borchert, R. V. Donner, R. V. Donner, J. Baehr

“…<p>We apply causal effect networks to evaluate the influence of spring North Atlantic extratropical sea surface temperatures (NA-SSTs) on the summer East Atlantic (EA) pattern seasonal predictability during the period of 1908–2008. …”
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HCAP: Hybrid cyber attack prediction model for securing healthcare applications. by Mohanad Faeq Ali, Mohammed Shakir Mohmood, Ban Salman Shukur, Rex Bacarra, Jamil Abedalrahim Jamil Alsayaydeh, Masrullizam Mat Ibrahim, Safarudin Gazali Herawan

“…The recurrent networks, specifically Long Short Term Memory (LSTM), process data from healthcare devices, identifying abnormal patterns that indicate potential cyberattacks over time. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…The review includes common methods such as convolutional neural networks, recurrent neural networks and generative adversarial networks, focusing on feature extraction techniques such as sequence features, image visualization and data enhancement. …”
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Optimization and Simulation of Flat Area Sites Based on Probability Matching and Transfer Intensity Using Remote Sensing Precipitation by Chen Yu, Huaiyong Shao, Xingchuan Yang, Gang Liu, Qi Xin, Jiaming Gu

“…Abstract The accuracy and continuity of records from rain gauge networks, as critical sources of precipitation data, directly influence the reliability of subsequent meteorological, land surface, and hydrological studies. …”
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The rise of exosome-mediated mechanisms in MSC therapy by Weihua Liu, Sheng Chen, Yuan Wang, Wei Gong

“…Despite the growing body of research, a comprehensive bibliometric evaluation of MSCs in GVHD is still lacking. Objective To perform a bibliometric analysis of global research on MSC-based therapies for GVHD using Citespace and VOSViewer, with the aim of mapping publication trends, collaboration networks, and emerging research hotspots. …”
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Non-destructive assessment of hemp seed vigor using machine learning and deep learning models with hyperspectral imaging by Damrongvudhi Onwimol, Pongsan Chakranon, Kris Wonggasem, Papis Wongchaisuwat

“…Deep learning models were trained on these selected wavelengths to directly learn patterns from the raw spectral data. The performance of these deep learning models was compared to traditional machine learning approaches. …”
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Efficient Sedimentary Facies Recognition Using Vision Transformer and Weakly Supervised Deep Multi-View Clustering by Hao Wu, Yu-Jie Dai, Xin-Yu Liu

“…Sedimentary facies recognition plays a crucial role in geological exploration and oil-gas resource evaluation. However, traditional recognition methods are limited by their ability to extract local features and efficiently utilize unlabeled data, making it difficult to effectively handle complex sedimentary facies characteristics. …”
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Research and analysis of the TCN-Multihead-Attention prediction model of landslide deformation in the Three Gorges Reservoir area, China by Huan Chen, Huan Chen, Yixuan Li, Yimin Liu

“…This paper proposes a TCN-Multihead-Attention prediction model for landslide deformation based on temporal convolutional networks (TCNs). We collected 8 years of monitoring data from the Huangniba Dengkan landslide in the Three Gorges Reservoir area, including surface deformation (horizontal displacement and elevation), rainfall, and reservoir levels. …”
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Reliable Breast Cancer Diagnosis with Deep Learning: DCGAN-Driven Mammogram Synthesis and Validity Assessment by Dilawar Shah, Mohammad Asmat Ullah Khan, Mohammad Abrar

“…This paper proposes a novel approach that utilizes deep convolutional generative adversarial networks (DCGANs) to effectively tackle the issue of limited data availability. …”
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation. by Soraya Khanmohmmadi, Toktam Khatibi, Golnaz Tajeddin, Elham Akhondzadeh, Amir Shojaee

“…<h4>Introduction</h4>Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. …”
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The functional near infrared spectroscopy applications in children with developmental diseases: a review by Jing Wang, Zhuo Zou, Haoyu Huang, Jinting Wu, Xianzhao Wei, Shuyue Yin, Yingjuan Chen, Yun Liu

“…Our synthesis uncovers distinct hemodynamic patterns associated with specific developmental disorders. …”
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Decoding vocal indicators of stress in laying hens: A CNN-MFCC deep learning framework by Suresh Neethirajan

“…This study leverages advanced Convolutional Neural Networks (CNNs) combined with Mel Frequency Cepstral Coefficients (MFCCs) to decode intricate vocalization patterns in laying hens experiencing acute environmental stress. …”
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Distinguishing Dyslexia, Attention Deficit, and Learning Disorders: Insights from AI and Eye Movements by Alae Eddine El Hmimdi, Zoï Kapoula

“…Machine learning models, including logistic regression, random forest, support vector machines, and neural networks, are trained using a GroupKFold strategy to ensure patient data are present in either the training or test set. …”
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Bibliometric analysis of the use of pathological techniques in camel research by Ahmed Aljazzar

“…However, there has been limited evaluation of research trends, thematic advancements, and international collaborations in this field. …”
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Machine learning-based analysis of defensive strategies in basketball using player movement data by Jianlong Li

“…The proposed hybrid model integrates LSTM to identify temporal features of players’ motion and CNN to recognize spatial patterns across the court. The model was trained and evaluated on the National Basketball Association’s (NBA) SportVU tracking data, which includes over 32,000 possessions. …”
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