Envelope and intelligent prediction of horizontal bearing capacity for offshore wind monopiles in sandy seabed under HM combined loading by Xin-Yu You, Shi-Yi Qian, Bin Li, Jun Wang, Ling-Yu Xu

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Comprehensive analysis of RNA methylation-related genes to identify molecular cluster for predicting prognosis and immune profiles in bladder cancer by Bo Li, Junlin Gan, Tinghao Li, Junrui Chen, Youlin Kuang, Jie Li, Hubin Yin

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Integrating UAV-Based Multispectral Data and Transfer Learning for Soil Moisture Prediction in the Black Soil Region of Northeast China by Tong Zhou, Shoutian Ma, Tianyu Liu, Shuihong Yao, Shenglin Li, Yang Gao

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Torque and speed prediction of a brushless direct current motor using nonlinear autoregressive with exogenous inputs and neural network by Muhammad Aseer Khan, Dur-e-Zehra Baig, Husan Ali, Fahad R. Albogamy

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Advanced battery management system enhancement using IoT and ML for predicting remaining useful life in Li-ion batteries by Gopal Krishna, Rajesh Singh, Anita Gehlot, Ahmad Almogren, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

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High-Resolution prediction of soil pH in European temperate forests using Sentinel-2 and ancillary environmental data by Haidi Abdullah, Andrew K. Skidmore, Andjin Siegenthaler, Elnaz Neinavaz

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Utilizing LSTM-GRU for IOT-Based Water Level Prediction Using Multi-Variable Rainfall Time Series Data by Indrastanti Ratna Widiasari, Rissal Efendi

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Artificial intelligence-based non-invasive bilirubin prediction for neonatal jaundice using 1D convolutional neural network by Fatemeh Makhloughi

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CytoLNCpred-a computational method for predicting cytoplasm associated long non-coding RNAs in 15 cell-lines by Shubham Choudhury, Naman Kumar Mehta, Gajendra P. S. Raghava

“…These cell-line specific models as well as web-based service are available to the public from our web server (https://webs.iiitd.edu.in/raghava/cytolncpred/).…”
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Modelling Resilience to Floods in Art Cities: A Historical Perspective by Chiara Arrighi, Fabio Castelli

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Deep Learning‐Based Prediction of Final Infarct Core from CT Perfusion Data: A Comparison to the Clinical Standard by Freda Werdiger, Milanka Visser, Chushuang Chen, Christina Lam, James Kolacz, Mark W. Parsons, Longting Lin, Christopher Levi, Andrew Bivard

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Application of state of health estimation and remaining useful life prediction for lithium-ion batteries based on AT-CNN-BiLSTM by Feng-Ming Zhao, De-Xin Gao, Yuan-Ming Cheng, Qing Yang

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Optimized landslide susceptibility prediction based on SBAS-InSAR: case study of the Jiuzhaigou Ms7.0 earthquake by Shiqian Yin, Zebing Dai, Ying Zeng

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Predicting EV battery state of health using long short term degradation feature extraction and FEA TimeMixer by Weijie Tang, Jiayan Chen, Dongjiao Chen

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Improving machine learning algorithm for risk of early pressure injury prediction in admission patients using probability feature aggregation by Shu-Chen Chang, Shu-Mei Lai, Mei-Wen Wu, Shou-Chuan Sun, Mei-Chu Chen, Chiao-Min Chen

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Identification of gastric cancer subtypes based on disulfidptosis-related genes: GPC3 as a novel biomarker for prognosis prediction by Nan Yi, Xindong Yin, Xiao Feng, Ming Ren, Chaoqun Ma

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The development of the pediatric NAFLD fibrosis score (PNFS) to predict the presence of advanced fibrosis in children with nonalcoholic fatty liver disease. by Naim Alkhouri, Sana Mansoor, Paola Giammaria, Daniela Liccardo, Rocio Lopez, Valerio Nobili

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Predicting the potential distribution of stingless bee, Tetragonula iridipennis in India using MaxEnt and CMIP6 climate projections by V. Karuppaiah, R. Maruthadurai, Bappa Das, P. S. Soumia, Ankush Gadge, Chandrashekhar Pote, Dhananjay Shirsat, Trupti Pandit, Sanket Sawant, S. V. Ramesh, Vijay Mahajan

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Clopidogrel response predicts thromboembolic events associated with coil embolization of unruptured intracranial aneurysms: A prospective cohort study. by Eiji Higashi, Shoji Matsumoto, Ichiro Nakahara, Taketo Hatano, Akira Ishii, Nobutake Sadamasa, Tsuyoshi Ohta, Takuma Ishihara, Keisuke Tokunaga, Mitsushige Ando, Hideo Chihara, Konosuke Furuta, Tetsuya Hashimoto, Koji Tanaka, Kazutaka Sonoda, Junpei Koge, Wataru Takita, Takuro Hashikawa, Yusuke Funakoshi, Daisuke Kondo, Takahiko Kamata, Atsushi Tsujimoto, Takuya Matsushita, Hiroyuki Murai, Keitaro Matsuo, Takanari Kitazono, Junichi Kira

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A benchmark of deep learning approaches to predict lung cancer risk using national lung screening trial cohort by Yifan Jiang, Leyla Ebrahimpour, Philippe Després, Venkata SK. Manem

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