Design and Development of Diabetes Management System Using Machine Learning by Robert A. Sowah, Adelaide A. Bampoe-Addo, Stephen K. Armoo, Firibu K. Saalia, Francis Gatsi, Baffour Sarkodie-Mensah

“…The model achieved specified goals by predicting with high accuracy, labels of new images. …”
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Machine learning unveils key Redox signatures for enhanced breast Cancer therapy by Tao Wang, Shu Wang, Zhuolin Li, Jie Xie, Kuiying Du, Jing Hou

“…We employed a comprehensive approach by combining ten distinct machine learning algorithms across 108 different combinations to scrutinize 88 pre-existing signatures of breast cancer. …”
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Experimental investigation of shaft misalignment effects on bearing reliability through vibration signal analysis using machine learning and deep learning by Fransiskus Tatas Dwi Atmaji, Jamasri, Hari Agung Yuniarto, I Made Miasa

“…Despite its practical importance, the direct impact of parallel shaft misalignment on bearing fault prediction remains unaddressed, mainly in the existing literature. …”
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Assessing current and future areas of ecological suitability for Lutzomyia shannoni in North America by Sydney DeWinter, Grace K. Nichol, Christopher Fernandez-Prada, Amy L. Greer, J. Scott Weese, Katie M. Clow

“…The objectives of this study were to predict the current and future ecological suitability of regions across North America for Lu. shannoni and to identify variables driving ecological suitability. …”
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Improved YOLOv8 Model for Phenotype Detection of Horticultural Seedling Growth Based on Digital Cousin by Yuhao Song, Lin Yang, Shuo Li, Xin Yang, Chi Ma, Yuan Huang, Aamir Hussain

“…Crop phenotype detection is a precise way to understand and predict the growth of horticultural seedlings in the smart agriculture era to increase the cost-effectiveness and energy efficiency of agricultural production. …”
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Design of a Conveyer Trough Bolt Signal Acquisition System and Bayesian Ensemble Identification Method for Working State by Yi Lian, Bangzhui Wang, Meiyan Sun, Kexin Que, Sijia Xu, Zhong Tang, Zhilong Huang

“…Finally, after comparing machine learning algorithms, Support Vector Machine was chosen for its superior performance. …”
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Non-invasive liver fibrosis markers are increased in obese individuals with non-alcoholic fatty liver disease and the metabolic syndrome by Anders Askeland, Rikke Wehner Rasmussen, Mimoza Gjela, Jens Brøndum Frøkjær, Kurt Højlund, Maiken Mellergaard, Aase Handberg

“…We used MRI (T1 relaxation times (T1) and liver stiffness), circulating biomarkers (CK18, PIIINP, and TIMP1), and algorithms (FIB-4 index, Forns score, FNI, and MACK3 score) to assess their potential in predicting liver fibrosis risk. …”
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Identification of M1 macrophage infiltration-related genes for immunotherapy in Her2-positive breast cancer based on bioinformatics analysis and machine learning by Sizhang Wang, Xiaoyan Wang, Jing Xia, Qiang Mu

“…Then, four overlapping M1 macrophage infiltration-related genes (M1 MIRGs), namely CCDC69, PPP1R16B, IL21R, and FOXP3, were obtained using five machine-learning algorithms. Subsequently, nomogram models were constructed to predict the incidence of Her2-positive breast cancer patients. …”
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Genomic profiling, implications for genotype-based treatment of 131 patients with phenylketonuria and characterization of novel p.Pro416Leu PAH variant by K. Klaassen, B. Kecman, S. Stankovic, J. Komazec, S. Pavlovic, Maja Stojiljkovic, M. Djordjevic

“…We detected one novel variant, p.Pro416Leu, which was classified as pathogenic, based on computational algorithms prediction, with destabilization as the mechanism of the effect upon PAH protein. …”
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Multi-Feature Fusion for Estimating Above-Ground Biomass of Potato by UAV Remote Sensing by Guolan Xian, Jiangang Liu, Yongxin Lin, Shuang Li, Chunsong Bian

“…Timely and accurate monitoring of above-ground biomass (AGB) is of great significance for indicating crop growth status, predicting yield, and assessing carbon dynamics. Compared with the traditional time-consuming and laborious method through destructive sampling, UAV remote sensing provides a timely and efficient strategy for estimating biomass. …”
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Oxidative balance is associated with diabetic kidney disease and mortality in adults with diabetes mellitus: Insights from NHANES database and Mendelian randomization by Li Jiang, Jie Jian, Xulin Sai, Hongda Yu, Wanxian Liang, Xiai Wu

“…The physical activity was identified as the core variable predicting DKD risk by two machine learning algorithms. …”
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A Reproducible Method for Donor Site Computed Tomography Measurements in Abdominally Based Autologous Breast Reconstruction by Damini Tandon, MD, Arthur Sletten, MD, PhD, Austin Ha, MD, Gary B. Skolnick, BA, MBA, Paul Commean, BEE, Terence Myckatyn, MD

“…Larger patient cohorts must be leveraged to determine correlations between abdominal CT scan findings and donor site outcomes using machine learning algorithms that generate models for predicting abdominal donor site complications.…”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat by Yidong Liu, Dali Ding, Mulai Tan, Yuequn Luo, Ning Li, Huan Zhou

“…The former combines missile attack zone calculation and trajectory prediction to optimize the control quantity of a single aircraft, while the latter uses fuzzy logic to analyze the overall situation of the three aircraft to drive tactical selection. …”
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The Agglomeration of Food Services and Their Colocation with Surrounding Complementary Services in the Guangdong–Hong Kong–Macao Greater Bay Area by Yixiao Wang, Xibo Wu, Jian Qin, Xiaoying Zhang, Xiangyu Wang

“…It investigates these issues within the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), utilizing point-of-interest (POI) data, spatial kernel density, the HDBSCAN clustering algorithm, and colocation quotients. The findings are as follows: (1) this research reveals a significant spatial agglomeration of food services near the Pearl River, with notable food clusters across administrative boundaries; (2) Guangzhou, Shenzhen, Foshan, and Dongguan provide a significant quantity of food services, while Hong Kong and Macao feature the highest percentages of foreign cuisine; (3) the colocation between food services and surrounding services is concentrated along the Pearl River; (4) leisure, education, and residential services are key factors attracting the proximity of food services; (5) leisure, education, retail, and tourism services exhibit the strongest attractiveness to Chinese food, while residential and healthcare services are closely linked to the distribution of snacks, and transportation services attract snacks and beverages.…”
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LSTM-JSO framework for privacy preserving adaptive intrusion detection in federated IoT networks by Shaymaa E. Sorour, Mohammed Aljaafari, Amany M. Shaker, Ahmed E. Amin

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Prognostic and therapeutic relevance of IL2RG-related LncRNAs in clear cell renal cell carcinoma by Weijing Hu, Bo Wu, Yongquan Chen, Xiaoling Guo, Xiaosong Wang, Dongwen Wang

“…The 6-IRLs model provides a robust tool for predicting prognosis and guiding therapeutic decisions.…”
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Round, just-below, or precise prices? Cultural differences in the prevalence of price endings in E-commerce by Alfio Ventura, Alfio Ventura, Alfio Ventura, Eve Sarah Troll, Meikel Soliman, David D. Loschelder

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Association of Obesity with Forearm Fractures, Bone Mineral Density and Fracture Risk (FRAX®) During Postmenopausal Period by Erkan Mesci, Nilgün Mesci, Afitap İçağasıoğlu, Ercan Madenci

“…It should be kept in mind that obesity may not necessarily be protective against fractures and treatment algorithms based solely on BMD might be inadequate to predict future fracture risk.…”
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An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments by Zhenling Dai, Ziqun Gu, Rongrong Shen, Jingshuai Wang

“…Notably, this 11-gene signature also predicted the sensitivity of breast cancer to both conventional and immune therapies, aligning closely with predictions from the OncoPredict algorithm. …”
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