USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTION MODELING IN THE PATIENTS WITH CONCURRENT HIV INFECTION AND TUBERCULOSIS IN THE PENITENTIARY SYSTEM by D. S. Ponomarev, S. A. Sterlikov, S. B. Ponomarev, E. L. Аveryanova

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Correction: Development and validation of a cardiovascular risk prediction model for Sri Lankans using machine learning. by Chamila Mettananda, Isuru Sanjeewa, Tinul Benthota Arachchi, Avishka Wijesooriya, Chiranjaya Chandrasena, Tolani Weerasinghe, Maheeka Solangaarachchige, Achila Ranasinghe, Isuru Elpitiya, Rashmi Sammandapperuma, Sujeewani Kurukulasooriya, Udaya Ranawaka, Arunasalam Pathmeswaran, Anuradhini Kasturiratne, Norihiro Kato, Rajitha Wickramasinghe, Prasanna Haddela, Janaka de Silva

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Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data by Yihang Zhou, Ruige Kong, Zhengsen Xu, Linlin Xu, Sibo Cheng

“…However, the selection of deep learning methods for wildfire prediction remains uncertain due to the lack of comparative analysis in a quantitative and explainable manner, crucial for improving prevention measures and refining models. …”
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Modeling for the Prediction and Evaluation of the Crimp Percentage of Plain Woven Fabric Based on Yarn Count and Thread Density by Kura Alemayehu Beyene, Chirato Godana Korra

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DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations by Yuyao Yan, Xinyi Chai, Jiajun Liu, Sijia Wang, Wenran Li, Tao Huang

“…Here we propose DeepMethyGene, an adaptive recursive convolutional neural network model based on ResNet that predicts gene expression using DNA methylation information. …”
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StatModPredict: A user-friendly R-Shiny interface for fitting and forecasting with statistical models. by Amanda Bleichrodt, Amelia Phan, Ruiyan Luo, Alexander Kirpich, Gerardo Chowell

“…<h4>Methods</h4>StatModPredict supports robust real-time forecasting and retrospective model analysis, including fitting, forecasting, evaluation, visualization, and comparison of results from four popular models. …”
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Integrating transcriptomic data with a novel drug efficacy prediction model for TCM active compound discovery by Yingcan Li, Yu Shen, Yezi Cai, Yulin zhang, Jiahui Gao, Lei Huang, Weinuo Si, Kai Zhou, Shan Gao, Qichao Luo

“…Abstract Identifying the active natural compounds remains a challenge for drug discovery, and new algorithms need to be developed to predict active ingredients from complex natural products. …”
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Construction of a clinically significant prostate cancer risk prediction model based on traditional diagnostic methods by Wen-Tong Ji, Yong-Kun Wang, Zhan-Yang Han, Si-Qi Wang, Yao Wang, Yao Wang

“…Subsequently, we developed an online calculator (https://jiwentong0.shinyapps.io/dynnomapp/) with six variables for biopsy optimization.ConclusionThis study incorporated the results of three traditional diagnostic methods to establish a cost-effective and highly accurate model for predicting csPCa before biopsy. …”
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MoLPre: A Machine Learning Model to Predict Metastasis of cT1 Solid Lung Cancer by Jie Lan, Heng Wang, Jing Huang, Weiyi Li, Min Ao, Wanfeng Zhang, Junhao Mu, Li Yang, Longke Ran

“…Furthermore, we embedded this model in a web application called MoLPre (https://molpre.cqmu.edu.cn/), a user‐friendly tool assisting in the metastasis prediction of cT1 solid lung cancer.…”
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A neural network based computational model to predict the output power of different types of photovoltaic cells. by WenBo Xiao, Gina Nazario, HuaMing Wu, HuaMing Zhang, Feng Cheng

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Application of multimodal large language models for safety indicator calculation and contraindication prediction in laser vision correction by Joon Yul Choi, Doo Eun Kim, Sung Jin Kim, Hannuy Choi, Tae Keun Yoo

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Machine learning models for accurately predicting properties of CsPbCl3 Perovskite quantum dots by Mehmet Sıddık Çadırcı, Musa Çadırcı

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PK/PD Modeling as a Tool for Predicting Bacterial Resistance to Antibiotics: Alternative Analyses of Experimental Data by M. V. Golikova, E. N. Strukova, Y. A. Portnoy, A. A. Firsov

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A multi-task learning model for global soil moisture prediction based on adaptive weight allocation by Yeguang li, Haiying Liu, Tianshan Lv

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A Hybrid Deep Learning Model Based on FFT-STL Decomposition for Ocean Wave Height Prediction by Yelian Sun, Longkun Yu, Dandan Zhu

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rbpTransformer: A novel deep learning model for prediction of piRNA and mRNA bindings. by Ahmet Gürhanlı

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Predicting the Development of a Low Gas-Saturated Zone of the Medvezhye Field Based on Geological and Hydrodynamic Modeling by Artem A. Shirjaev, Kirill E. Vinogradov, Y. V. Vaganov, Vitaliya O. Naumenko

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Using ARCH and GARCH mathematical models to predict the general budget deficit for the period from (2008) to (2023) by Saad Obaid Jameel AL-Masoodi

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Analysis and Prediction of Traffic Conditions Using Machine Learning Models on Ikorodu Road in Lagos State, Nigeria by Udeme Udo Imoh, Majid Movahedi Rad

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Near‐Resonant Generation of Internal Tide Superharmonics: Comparing Theoretical Predictions With a Global Ocean Model by L. E. Baker, A. Doak, D. Bi

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