Personalized glucose prediction using in situ data only by Rohan Singh, Marouane Toumi, Marcel Salathé

“…Here, we show that a machine learning algorithm with such real-world data (RWD) collected from a digital cohort with over 1,000 participants can achieve high accuracy in PPGR prediction. …”
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Enhancing Relationship Link Prediction With Hierarchical Feature Enhancement by Zhouying Xu, Huiyue Wang

“…In this study, we endeavor to assess the potential for establishing friendships between users, a challenge that intersects with the domains of friend recommendation and link prediction. Notably, prevailing models in friend recommendation predominantly consider only the attributes of users, whereas link prediction models primarily emphasize network structure. …”
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Discrimination Analysis for Predicting Defect-Prone Software Modules by Ying Ma, Ke Qin, Shunzhi Zhu

“…By combating these two problems, we propose an algorithm based on kernel discrimination analysis called KDC to build more effective prediction model. …”
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Agricultural big data for predicting crop water demand by Zhongbo Liu, Guillermo Palacios-Navarro, Raquel Lacuesta

“…And using K-MEANS, KNN, Random Forest algorithm to mine the generated big data, and finally scientifically predict the water demand for crop growth in agricultural tomato greenhouses at 25–35° angles in Ningxia, China, the results show that the research results effectively predict the water demand of crops in this type of agricultural greenhouses in the region, and provide a reference to the prediction of water demand for other crops in the similar greenhouses in the region, as well as to the Water saving prediction of crops in agricultural greenhouses in the region, rational planning of water resource utilization, and development of scientific and reasonable irrigation system for agricultural greenhouses are all important references.…”
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Leveraging haplotype information in heritability estimation and polygenic prediction by Jonas Meisner, Michael Eriksen Benros, Simon Rasmussen

“…We introduce a framework, named hapla, with a novel algorithm for clustering haplotypes in phased genotype data to estimate heritability and perform reference-free polygenic prediction in complex traits. …”
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Using artificial intelligence tools to predict and alleviate poverty by Ghada Alturif, Wafaa Saleh, Alaa A. El-Bary, Radwa Ahmed Osman

“…A one-dimensional Convolutional Neural Network (1D-CNN) is used in the model to examine and extract patterns from historical socio-economic data from 2000 to 2022. The algorithm uses deep learning techniques to efficiently extract temporal correlations from the data, allowing for accurate predictions of each country's progress towards ending poverty and raising living standards. …”
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Enhancing molecular property prediction with quantized GNN models by Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije

“…This paper presents a systematic approach to molecular networks by integrating GNN models with the DoReFa-Net quantization algorithm. The proposed method aims to enhance computational efficiency while maintaining predictive performance, enabling lightweight yet effective models suitable for molecular task. …”
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Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

“…This study proposes a rockburst risk prediction method based on the SSA-CNN-MoLSTM-Attention model. …”
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Software pipeline for predicting and analyzing the structure of the receptor–ligand by A.S. Kozlova, A.R. Mukhametgalieva, A.N. Fattakhova, N.I. Akberova

“…Such a pipeline involves a complex algorithm, from predicting the structure of the receptor to searching and analyzing the interaction of ligands with the receptor. …”
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Overlap matrix completion for predicting drug-associated indications. by Mengyun Yang, Huimin Luo, Yaohang Li, Fang-Xiang Wu, Jianxin Wang

“…We then propose the OMC2 algorithm to fill out the values of the missing entries in these two adjacency matrices, and predict the scores of unknown drug-disease pairs. …”
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Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children by Satrio Agung Wicaksono, Satrio Hadi Wijoyo, Fatmawati Fatmawati, Tri Afirianto, Diva Kurnianingtyas, Mochammad Chandra Saputra

“…Addressing this issue requires an effective approach to predicting and preventing inadequate nutritional fulfillment. …”
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Review of Research on Trajectory Prediction of Road Pedestrian Behavior by YANG Zhiyong, GUO Jieru, GUO Zihang, ZHANG Ruixiang, ZHOU Yu

“…This paper also reviews commonly used datasets and evaluation metrics in the field, providing a thorough evaluation of current algorithmic performance. Finally, it addresses the challenges in pedestrian trajectory prediction for autonomous driving, particularly the dynamic coupling between pedestrians with multi-directional traffic and infrastructure, offering potential solutions and discussing future research directions.…”
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EFFICIENCY OF RAW GLUTEN CONTENT PREDICTION IN WHEAT KERNELS by A. V. Pasynkov, E. N. Pasynkova

“…There have been developed and presented an algorithm and results of testing the predictive capabilities of the equation based on independent data. …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Software defect prediction (SDP) is used to identify defects in software modules that can be a challenge in software development. …”
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Correlation and Prediction Analysis of Cyanobacteria with Water Environment Data by Sang-Leen Yun

“…Furthermore, cyanobacteria occurrence was predicted using a random forest algorithm, with a linear regression model serving as a baseline for comparison. …”
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Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

“…To accurately and efficiently predict the stability state of slopes, we propose a combined model that integrates the Newton–Raphson optimization algorithm (NRBO) with an optimized extreme gradient boosting tree (XGBoost). …”
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Machine learning prediction of pKa of organic acids by Juda Baikété, Alhadji Malloum, Jeanet Conradie

“…The model trained with the ExTr algorithm showed the best prediction performance with an overall mean absolute error (MAE) value of 1.41 pKa units. …”
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Pathway activation model for personalized prediction of drug synergy by Quang Thinh Trac, Yue Huang, Tom Erkers, Päivi Östling, Anna Bohlin, Albin Osterroos, Mattias Vesterlund, Rozbeh Jafari, Ioannis Siavelis, Helena Backvall, Santeri Kiviluoto, Lukas Orre, Mattias Rantalainen, Janne Lehtiö, Soren Lehmann, Olli Kallioniemi, Yudi Pawitan, Trung Nghia Vu

“…Computational models based on the integration of omics data have been used to identify synergistic combinations, but predicting drug synergy remains a challenge. Here, we introduce Drug synergy Interaction Prediction (DIPx), an algorithm for personalized prediction of drug synergy based on biologically motivated tumor- and drug-specific pathway activation scores (PASs). …”
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Prediction of Clinical Bronchiectasis from Asymptomatic Radiological Bronchiectasis by Fan Y, Li Z, Jiang N, Zhou Y, Song J, Yu F, Zhang J, Wang X

“…ROC, a calibration and decision curve were used to assess the predictive performance of our new prediction model.Results: 370 patients (74, 20% with CB) were finally included. …”
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Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO by Adel Taieb, Moêz Soltani, Abdelkader Chaari

“…This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO) Fuzzy Optimal Model Predictive Control (FOMPC) using the Adaptive Particle Swarm Optimization (APSO) algorithm. …”
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