Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…The model enhances reservoir characterization by capturing complex lithological patterns, supporting better zonation and well placement. …”
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Advanced and interpretable corneal staining assessment through fine grained knowledge distillation by Yuqing Deng, Pujin Cheng, Ruiwen Xu, Lirong Ling, Hongliang Xue, Shiyou Zhou, Yansong Huang, Junyan Lyu, Zhonghua Wang, Kenneth K. Y. Wong, Yimin Zhang, Kang Yu, Tingting Zhang, Xiaoqing Hu, Xiaoyi Li, Xiaoying Tang, Yan Lou, Jin Yuan

“…Additionally, FKD-CSS demonstrated generalizability in multi-ocular-surface-disease testing, underscoring its potential in handling different staining patterns.…”
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Pertussis clinical profile shift, severity, prediction in a tertiary hospital: A comparative study before, during, and after COVID-19 in Southern China by Shufeng Tian, Yulan Chen, Qiru Su, Biao Sun, Zengrui Lin, Yuchun Long, Hongmei Wang, Cuijuan Liao, Ying Zhang, Jinjun Zheng, Lvjun Chen, Song Guan, Sen Wang, Xinlei Xu, Jingwen Ai, Wenhong Zhang, Jikui Deng

“…Analysis included changes in demographic and clinical features, indicators of severe cases, and resistance patterns over the study period. …”
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NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides by Chengzhi Xie, Yijie Wei, Xinwei Luo, Huan Yang, Hongyan Lai, Fuying Dao, Juan Feng, Hao Lv

“…NeXtMD systematically extracts four functionally relevant sequence-derived descriptors—residue composition, inter-residue correlation, physicochemical properties, and sequence patterns—and utilizes a two-stage prediction strategy. …”
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Optimization of CNN Activation Functions using Xception for South Sulawesi Batik Classification by Aswan Aswan, Eva Yulia Puspaningrum, Billy Eden William Asrul

“…The results demonstrate that selecting an optimal activation function substantially enhances convolutional neural network classification of complex batik patterns. The findings offer practical guidance for development of resource aware batik identification systems in support of cultural digitization and education initiatives.…”
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Advancing state of health estimation for electric vehicles: Transformer-based approach leveraging real-world data by Kosaku Nakano, Sophia Vögler, Kenji Tanaka

“…While the study is constrained by a dataset featuring repetitive driving patterns, it highlights the significant potential of transformer for SOH estimation in EVs and offers valuable insights for future data collection and model development.…”
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MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…These datasets serve two functions: improving illness prediction and examining large data reservoirs to identify previously unknown disease patterns. Leveraging deep learning models, it becomes feasible to detect and forecast the early stages of numerous diseases based on individual health conditions. …”
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TableBorderNet: A Table Border Extraction Network Considering Topological Regularity by Jing Yang, Shengqiang Zhou, Xialing Li, Yuchun Huang, Honglin Jiang

“…Additionally, a generative self-supervised strategy simulates common degradation patterns, allowing the model to achieve strong performance with minimal reliance on manually annotated data. …”
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Emotional resonance and rational reflection in hybrid space: a cross-platform study of public opinion evolution in youth digital collective action by Jia Jia Hao, Xiaotong Dong, Yingyue Li, Shuang Li

“…Grounded in collective action theory and urban social movement theory within hybrid space, this research uncovered the organizational logic and cross-platform expression patterns of emergent youth collective action in social media contexts. …”
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A Comprehensive Review of EEG-Based Seizure Detection Techniques by Goldwyn Sudhakar Jebaraj, Konguvel Elango

“…Despite considerable progress in EEG signal acquisition, preprocessing methodologies, and the application of machine learning algorithms, significant challenges persist due to the inherent complexity and inter-subject variability observed in seizure patterns. This review aims to provide guidance for new researchers in this field, starting with the fundamental aspects of epilepsy, encompassing its diverse clinical presentations (syndromes), associated health conditions (comorbidities), and characteristic EEG manifestations. …”
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Interpretable Deep Learning for Diabetic Retinopathy: A Comparative Study of CNN, ViT, and Hybrid Architectures by Weijie Zhang, Veronika Belcheva, Tatiana Ermakova

“…The models are assessed based on classification accuracy and interpretability, applying Grad-CAM and Attention-Rollout to analyze decision-making patterns. Results indicate that hybrid models outperform both standalone CNNs and ViTs, achieving a better balance between local feature extraction and global context awareness. …”
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Time-series and deep learning approaches for renewable energy forecasting in Dhaka: a comparative study of ARIMA, SARIMA, and LSTM models by Mohammad Liton Hossain, S. M. Nasif Shams, Saeed Mahmud Ullah

“…The ARIMA(2,1,2) and SARIMA(2,1,2)(1,1,1,24) models captured basic temporal patterns but struggled with non-linear dynamics, achieving R2 scores of − 0.0008 and − 0.1104, respectively. …”
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Synchronized Survey Scan Approach Allows for Efficient Discrimination of Isomeric and Isobaric Compounds during LC-MS/MS Analyses by Keabetswe Masike, Ntakadzeni Madala

“…Thus, the method was shown to distinguish (by differences in fragmentation patterns) between diCQA and their isobars, caffeoylquinic acid (CQA) glycosides. …”
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A Graph Representation Learning-Based Method for Event Prediction by Xi Zeng, Guangchun Luo, Ke Qin, Pengyi Zheng

“…Predicting events allows for the exploration of the developmental trajectories and summarization of patterns associated with these events. …”
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Deep Learning‐Based 3D Microseismic Event Direct Location Using Simultaneous Surface and Borehole Data by Yuanyuan Yang, Omar M. Saad, Tariq Alkhalifah

“…Abstract Microseismic monitoring is crucial for characterizing and assessing fracture systems developed during subsurface operations like geothermal reservoir development, CO2 sequestration, and hydraulic fracturing. …”
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CircDock6 drives metabolic dysfunction–associated steatotic liver disease progression in mice and mouse hepatocytes via mmu-let-7g-5p/insulin-like growth factor 1 receptor regulati... by Hongpeng Lu, Xiaoyun Ding, Peifei Li

“…Objective Circular RNAs belong to a category of noncoding RNAs that feature a unique continuous, covalently bonded ring configuration. …”
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Meteorological Assessment of Vertical Axis Wind Turbine Energy Microgeneration Potentials Across Two Swiss Cities Located in Complex Terrain by Aldo Brandi, Gabriele Manoli

“…These results highlight the need for research on urban wind energy featuring detailed city‐scale assessments that account for urban heterogeneities and regional circulation patterns, to inform future planning investments and engineering development.…”
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Imaging-based assessment of response to olaparib in platinum-sensitive relapsed ovarian cancer patients by Maria Delgado-Ortet, Maria Delgado-Ortet, Vlad Bura, Vlad Bura, Vlad Bura, Vlad Bura, Ionut-Gabriel Funingana, Ionut-Gabriel Funingana, Ionut-Gabriel Funingana, Ionut-Gabriel Funingana, David Hulse, David Hulse, David Hulse, Leonardo Rundo, Leonardo Rundo, Leonardo Rundo, James D. Brenton, James D. Brenton, James D. Brenton, James D. Brenton, Evis Sala, Evis Sala, Evis Sala, Evis Sala, Evis Sala, Lorena Escudero Sanchez, Lorena Escudero Sanchez

“…Anatomical networks of the metastatic sites were constructed to represent patterns of disease distribution. Volume and first-order radiomic features were computed and compared to different assessments of treatment response.ResultsThe average number of edges per patient in the anatomical networks and total volumetric burden decreased with treatment were measured, differentiating between responders and nonresponders. …”
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Mitigating malicious denial of wallet attack using attribute reduction with deep learning approach for serverless computing on next generation applications by Amal K. Alkhalifa, Mohammed Aljebreen, Rakan Alanazi, Nazir Ahmad, Sultan Alahmari, Othman Alrusaini, Ali Alqazzaz, Hassan Alkhiri

“…The deep learning (DL) model, a part of the machine learning (ML) technique, has developed as an effectual device in cybersecurity, permitting more effectual recognition of anomalous behaviour and classifying patterns indicative of threats. …”
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Acute Liver Injury Is Independent of B Cells or Immunoglobulin M. by James A Richards, Martina Bucsaiova, Emily E Hesketh, Chiara Ventre, Neil C Henderson, Kenneth Simpson, Christopher O C Bellamy, Sarah E M Howie, Stephen M Anderton, Jeremy Hughes, Stephen J Wigmore

“…<h4>Background & aims</h4>Acute liver injury is a clinically important pathology and results in the release of Danger Associated Molecular Patterns, which initiate an immune response. Withdrawal of the injurious agent and curtailing any pathogenic secondary immune response may allow spontaneous resolution of injury. …”
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