Modulating Cognition-Linked Histone Acetyltransferases (HATs) as a Therapeutic Strategy for Neurodegenerative Diseases: Recent Advances and Future Trends by Huong Anh Mai, Christina M. Thomas, Gu Gu Nge, Felice Elefant

Get full text

Node-Based Graph Convolutional Network With SLIC Method for Breast Cancer Ultrasound Images Classification by Kien Trang, Fung Fung Ting, Bao Quoc Vuong, Chee-Ming Ting

“…Utilizing the Simple Linear Iterative Clustering (SLIC) algorithm, superpixels are segmented and treated as nodes and connected based on color similarity and spatial proximity. …”
Get full text

Explainable Artificial Intelligence for predicting the compressive strength of soil and ground granulated blast furnace slag mixtures by Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, Nor Zurairahetty Mohd Yunus, Nadiah Jamaludin, Elamin Mutaz, Hashim Elshafie, Mosab Hamdan

“…The XGB model emerged as the most effective predictor of unconfined compressive strength for soil treated with GGBS, accounting for over 90% of the variance explained by independent factors. …”
Get full text

Finite-size effects in molecular simulations: a physico-mathematical view by Benedikt M. Reible, Carsten Hartmann, Luigi Delle Site

“…Here this feature is treated employing the same statistical mechanics framework developed for the first problem.…”
Get full text

Development of a Diagnostic Prediction Model for Post‐Stroke Cognitive Impairment in Acute Large Vessel Occlusion Stroke Using Multimodal MRI and PET/CT: A Study Protocol by Junhao Li, Yuding Luo, Pingchuan Liu, Jiali Zhang, Chuanxi Duan, Hai Xiong, Maoxia Li, Binyang Zhang, Lu Li, Lulu Gong, Yupeng Niu, Bo Zheng, Jian Wang

“…Conclusion: This study will develop a PSCI prediction model based on multimodal imaging and clinical data in EVT‐treated LVO‐AIS patients, providing a tool for early diagnosis and personalized interventions. …”
Get full text

Neural Network-Based Temporal Ensembling of Water Depth Estimates Derived from SuperDove Images by Milad Niroumand-Jadidi, Carl J. Legleiter, Francesca Bovolo

Get full text

Abusive Head Trauma Module in the Child Abuse Pediatrics Curriculum for Physicians (CAP-CuP): Rehma's Story by Katie L. Johnson, Caitlin E. Crumm, Emily C. B. Brown

Get full text

A Bioelectrically Enabled Smart Bandage for Accelerated Wound Healing and Predictive Monitoring by Ahmad F. Turki, Aziza R. Alrafiah

“…Vital signs including heart rate (BPM), oxygen saturation (SpO₂), and temperature were monitored continuously. Machine learning models were trained on these data to predict wound healing status. …”
Get full text

PGHDR: Dynamic HDR reconstruction with progressive feature alignment and quality-guided fusion by Ying Qi, Qiushi Li, Zhaoyuan Huang, Jian Li, Chenyang Wang, Teng Wan, Qiang Zhang

“…The core innovation is a learning paradigm that jointly optimizes motion estimation and alignment quality perception. …”
Get full text

Microstructural characterization and hardness prediction of AlCuCrFeNi high entropy alloys using Transformer-based Physics-Informed Neural Networks (T-PINN) by Mohamed Yasin Abdul Salam, Enoch Nifise Ogunmuyiwa, Victor Kitso Manisa, Abid Yahya, Irfan Anjum Badruddin

“…Synthesized alloys were heat-treated at different temperatures to enhance phase stability, induce microstructural evolution and hardness performance. …”
Get full text

Application of predictive models in boosting power of Alzheimer's disease clinical trials: A post hoc analysis of phase 3 solanezumab trials by Ali Ezzati, Christos Davatzikos, David A. Wolk, Charles B. Hall, Christian Habeck, Richard B. Lipton

“…Result In EXPEDITION, 46.3% of placebo‐treated patients showed no cognitive decline and the proportion was similar in EXPEDITION2 (45.6%). …”
Get full text

Optimal mean arterial pressure for favorable neurological outcomes in patients after cardiac arrest by Sijin Lee, Kwang-Sig Lee, Kap Su Han, Juhyun Song, Sung Woo Lee, Su Jin Kim

“…Methods This retrospective observational study included 291 post-cardiac arrest patients treated at a tertiary care center. Five machine learning models to predict favorable neurological outcomes using hourly MAP measurements during the first 24 h after return of spontaneous circulation (ROSC) were compared and Random Forest model was selected due to its superior performance. …”
Get full text

Single-cell atlas of human gingiva unveils a NETs-related neutrophil subpopulation regulating periodontal immunity by Wei Qiu, Ruiming Guo, Hongwen Yu, Xiaoxin Chen, Zehao Chen, Dian Ding, Jindou Zhong, Yumeng Yang, Fuchun Fang

“…Animal models of periodontitis were treated with NETs inhibitors to investigate the effects of NETs in severe periodontitis. …”
Get full text

Lesion Volume as a Predictor for Return to Work After Endovascular Treatment: A 4‐Year Prospective Cohort Study by Gisle Berg Helland, Mona Kristiansen Beyer, Brian Anthony B. Enriquez, Hege Ihle‐Hansen, Håkon Ihle‐Hansen, Stein Andersson, Esten Høyland Leonardsen, Helle Stangeland, Bettina Ùjhelyi, Guri Hagberg, Hanne Flinstad Harbo, Anne Hege Aamodt, Einar August Høgestøl

“…Notably, the most influential feature in the machine learning model for predicting RTW was lesion volume. …”
Get full text

A Hybrid, Non‐Stationary Stochastic Watershed Model (SWM) for Uncertain Hydrologic Simulations Under Climate Change by Zach Brodeur, Sungwook Wi, Ghazal Shabestanipour, Jon Lamontagne, Scott Steinschneider

“…We fit one hydrologic model to historical observations, and then fit a second model to the simulations of the first, treating the first model as the true hydrologic system. …”
Get full text

Health Modeling — An Innovative Educational Program for the General Medicine Specialty by M. M. Litvinova, M. S. Khamidulina, T. M. Litvinova, Yu. A. Lutokhina, E. N. Dudnik, N. V. Kireeva, K. V. Ivashkin, B. A. Volel

“…In the senior years, the learning trajectory is individualized, and students acquire healthcare management skills through internships in federal and regional healthcare institutions. …”
Get full text

Targeting PFKFB3 to restore glucose metabolism in acute pancreatitis via nanovesicle delivery by Hai Jiang, Zhipeng Xu, Qi Song, Junjie Tao, Jia Liu, Qiang Wang, Huaisheng Zhang, Heng Zhu, Qiliang Li, Lei Li

Get full text

Direction of arrival estimation in passive radar based on deep neural network by Xiaoyong Lyu, Jun Wang

“…The RDCC result is taken as the input of the deep learning method, and the amplitude and phase uncertainties of the RDCC result are treated. …”
Get full text

Ordinal Random Tree with Rank-Oriented Feature Selection (ORT-ROFS): A Novel Approach for the Prediction of Road Traffic Accident Severity by Bita Ghasemkhani, Kadriye Filiz Balbal, Kokten Ulas Birant, Derya Birant

Get full text

Auto regressive neural network-driven reliability optimization in base-isolated building design by John Thedy, Kuo-Wei Liao, Taeyong Kim

Get full text