Nutritional intake of micronutrient and macronutrient and type 2 diabetes: machine learning schemes by Mohammad Rashidmayvan, Amin Mansoori, Elahe Derakhshan-Nezhad, Davoud Tanbakuchi, Fatemeh Sangin, Maryam Mohammadi-Bajgiran, Malihehsadat Abedsaeidi, Sara Ghazizadeh, MohammadReza Mohammad Taghizadeh Sarabi, Ali Rezaee, Gordon Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…We aimed to investigate the relationship between intake of macro/micronutrients and the incidence of type 2 diabetes (T2D) using logistic regression (LR) and a decision tree (DT) algorithm for machine learning. Method Our research explores supervised machine learning models to identify T2D patients using the Mashhad Cohort Study dataset. …”
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A machine learning-based model for predicting paroxysmal and persistent atrial fibrillation based on EHR by Yuqi Zhang, Sijin Li, Peibiao Mai, Yanqi Yang, Niansang Luo, Chao Tong, Kuan Zeng, Kun Zhang

“…We aim to develop a predictive model using a machine learning algorithm for identification of paroxysmal and persistent AF, and investigate the influencing factors. …”
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A Novel Method for Screening the PMU Phase Angle Difference Data Based on Hyperplane Clustering by Ancheng Xue, Shuang Leng, Yecheng Li, Feiyang Xu, Kenneth E. Martin, Jingsong Xu

“…Field data can suffer from errors, such as time synchronization error, transducer error, PMU algorithm error, hardware error or malicious attacks, etc. …”
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Association of delayed asthma diagnosis with asthma exacerbations in children by Chung-Il Wi, MD, Euijung Ryu, PhD, Katherine S. King, MS, Jung Hyun Kwon, MD, PhD, Joshua T. Bublitz, BS, Miguel Park, MD, Sergio E. Chiarella, MD, Jason D. Greenwood, MD, MS, Thanai Pongdee, MD, Lynnea Myers, PhD, Björn Nordlund, PhD, Sunghwan Sohn, PhD, Elham Sagheb, MS, Bhavani Singh Agnikula Kshatriya, MS, Dave Watson, PhD, Hongfang Liu, PhD, Beverley J. Sheares, MD, MS, Carla M. Davis, MD, Wade Schulz, MD, PhD, Young J. Juhn, MD, MPH

“…We defined onset date as the date when subjects first met predetermined asthma criteria ascertained by an electronic health records–based natural language processing algorithm. Delay in diagnosis (DD) was defined as first diagnosis >30 days from onset date (vs timely diagnosis [TD] within 30 days). …”
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Exploring the process—structure–property relationship of nylon aramid 3D printed composites and parameter optimization using supervised machine learning techniques by Mohammed Raffic Noor Mohamed, Ganesh Babu Karuppiah, Dharani Kumar Selvan, Rajasekaran Saminathan, Shubham Sharma, Shashi Prakash Dwivedi, Sandeep Kumar, Mohamed Abbas, Dražan Kozak, Jasmina Lozanovic

“…In an 80:20 train-test split, the decision tree approach outperformed the k -nearest neighbor algorithm for all four output responses, with classification accuracy ranging from 83.33% to 100%. …”
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Evaluating the spatiotemporal patterns of GPP and tree growth for their response to CO2 fertilization effects in mid-latitude forests of China by Bin Wang, Xiangqi Kong, Shaojie Bian, Ying Quan, Zechuan Wu, Jianyang Liu, Mingze Li

“…This was combined with the random forest algorithm and a moving window approach to assess the spatiotemporal patterns of vegetation productivity and tree growth responses to atmospheric CO2 variations between 1982 and 2015. …”
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Enhancing environmental models with a new downscaling method for global radiation in complex terrain by A. Druel, J. Ruffault, H. Davi, A. Chanzy, O. Marloie, M. De Cáceres, A. Olioso, F. Mouillot, C. François, K. Soudani, N. K. Martin-StPaul

“…The model was evaluated by comparing simulated and observed radiation at the Mont Ventoux study site (southeast of France) using the recent ERA5-Land hourly data available at a 9 km resolution as input and downscaled to different spatial resolutions (from 1 km to 30 m resolution) using a DEM. The downscaling algorithm improved the reliability of radiation at the study site, in particular at scales below 150 m. …”
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An AI-Based Digital Scanner for <i>Varroa destructor</i> Detection in Beekeeping by Daniela Scutaru, Simone Bergonzoli, Corrado Costa, Simona Violino, Cecilia Costa, Sergio Albertazzi, Vittorio Capano, Marko M. Kostić, Antonio Scarfone

“…This study introduces a digital portable scanner coupled with an AI algorithm (BeeVS) used to detect Varroa mites. The device works through image analysis of a sticky sheet previously placed under the beehive for some days, intercepting the Varroa mites that naturally fall. …”
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The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC) repository: rationale and blueprint by Hakim Baazaoui, Stefan T. Engelter, Stefan T. Engelter, Stefan T. Engelter, Henrik Gensicke, Henrik Gensicke, Henrik Gensicke, Lukas S. Enz, Lukas S. Enz, Marios Psychogios, Marios Psychogios, Matthias Mutke, Matthias Mutke, Patrik Michel, Davide Strambo, Alexander Salerno, Henk A. Marquering, Paul J. Nederkoorn, Nabila Wali, Stephanie Tanadini-Lang, Björn Menze, Ezequiel de la Rosa, Kaiyuan Yang, Gian Marco De Marchis, Gian Marco De Marchis, Tolga D. Dittrich, Tolga D. Dittrich, Francesco Valletta, Francesco Valletta, Manon Germann, Carlo W. Cereda, João Pedro Marto, Lisa Herzog, Patrick Hirschi, Zsolt Kulcsar, Susanne Wegener, Susanne Wegener

“…There, patient identifiers are removed and images are algorithmically de-faced. De-identified structured clinical data are connected to the imaging data by a new identifier. …”
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MRI-based deep learning and radiomics for predicting the efficacy of PD-1 inhibitor combined with induction chemotherapy in advanced nasopharyngeal carcinoma: A prospective cohort... by Yiru Wang, Fuli Chen, Zhechen Ouyang, Siyi He, Xinling Qin, Xian Liang, Weimei Huang, Rensheng Wang, Kai Hu

“…From MRI scans, DLFs and conventional radiomic characteristics were recovered. The random forest algorithm was employed to identify the most valuable features. …”
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Vehicle Turn Pattern Counting and Short Term Forecasting Using Deep Learning for Urban Traffic Management System by Sundarakrishnan Narayanan, Sohan Varier, Tarun Bhupathi, Manaswini Simhadri Kavali, Mohana, P. Ramakanth Kumar, K. Sreelakshmi

“…Building on this, we designed a custom vehicle counting algorithm that integrated the BoT-SORT tracker with dynamic counting boxes, accurately capturing vehicle movements and turn patterns in real-time and this integrated approach attained a best deviation of 20.79%. for turn pattern counting and 28.41% for forecasting. …”
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The dynamics of lowland river sections of Danube and Tisza in the Carpathian basin by Imre M. Jánosi, Imre M. Jánosi, István Zsuffa, István Zsuffa, Tibor Bíró, Boglárka O. Lakatos, Boglárka O. Lakatos, András Szöllősi-Nagy, Zsolt Hetesi, Zsolt Hetesi

“…Extracted periods by the Lomb-Scargle algorithm (suitable for unevenly sampled time series) and the long-time means indicate the expected annual seasonality. …”
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Transoral endoscopic thyroid lobectomy and ipsilateral central neck lymph node dissection vestibular approach: analysis of the learning curve and clinical outcomes evaluation by Yuhang Deng, Jiaojiao Zhao, Mei Tao, Haixin Zhao, Ruoxin Fan, Xiaoming Wang, Xiubo Lu

“…Utilizing the CUSUM algorithm, two distinct learning phases were delineated: the exploration phase, comprising 58 cases, and the maturation phase, encompassing 137 cases. …”
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Machine vision-based detection of key traits in shiitake mushroom caps by Jiuxiao Zhao, Jiuxiao Zhao, Wengang Zheng, Wengang Zheng, Yibo Wei, Yibo Wei, Qian Zhao, Qian Zhao, Jing Dong, Jing Dong, Xin Zhang, Xin Zhang, Mingfei Wang, Mingfei Wang

“…Finally,M3 group using GWO_SVM algorithm achieved optimal performance among six mainstream machine learning models tested with an R²value of 0.97 and RMSE only at 0.038 when comparing predicted values with true values. …”
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The Suitability of the CdC field Triage for Korean Trauma Care by Kang Kook Choi, Myung Jin Jang, Min A Lee, Gil Jae Lee, Byungchul Yoo, Youngeun Park, Jung Nam Lee

“…The Korean trauma system (established in 2014) uses the trauma field triage algorithm of the United States Centers for Disease Control and Prevention (CDC). …”
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Quality identification of Amomi fructus using E-nose, HS-GC-IMS, and intelligent data fusion methods by Pan-Pan Zhang, Xin-Jing Gui, Xin-Jing Gui, Xin-Jing Gui, Xue-Hua Fan, Han-Li, Hai-Yang Li, Xiao-Peng Li, Feng-Yu Dong, Yan-Li Wang, Jing-Yao, Jing-Yao, Jun-Han Shi, Jun-Han Shi, Rui-Xin Liu, Rui-Xin Liu, Rui-Xin Liu, Rui-Xin Liu, Rui-Xin Liu

“…In conclusion, the intelligent data fusion algorithm based on E-nose and HS-GC-IMS data effectively identifies the authenticity, origin, and provenance of AF, providing a rapid and accurate method for quality evaluation.…”
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Gottron's carcinoid papillomatosis of the skin (сlinical case) by O.M. Biesiedin, V.M. Shkuropat, K.V. Tsygankov, P.O. Hrytsenko, S.V. Biletska

“…The lack of a clear understanding of the diagnostic and treatment algorithm creates additional difficulties in the treatment of Gottron's carcinoid papillomatosis of the skin. …”
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An Ultrasound-Based Non-Invasive Blood Pressure Estimation Method Based on Optimal Vascular Wall Tracking Position by Liyuan Liu, Xingguang Geng, Fei Yao, Yitao Zhang, Haiying Zhang, Yunfeng Wang, Zhaoying Zheng

“…To validate the effectiveness of the proposed algorithm, 25 volunteers participated in the study. …”
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Caution when using network partners for target identification in drug discovery by Dandan Tan, Yiheng Chen, Yann Ilboudo, Kevin Y.H. Liang, Guillaume Butler-Laporte, J. Brent Richards

“…We used the IntAct database to find physically interacting proteins of genes identified by exome-wide association studies (ExWASs), genome-wide association studies (GWASs) combined with a locus-to-gene mapping algorithm called the Effector Index, and Genetic Priority Score (GPS), which integrated eight genetic features with drug indications from the Open Targets and SIDER databases. …”
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Prediction of microvascular obstruction from angio-based microvascular resistance and available clinical data in percutaneous coronary intervention: an explainable machine learning... by Zhe Zhang, Yang Dai, Peng Xue, Xue Bao, Xinbo Bai, Shiyang Qiao, Yuan Gao, Xuemei Guo, Yanan Xue, Qing Dai, Biao Xu, Lina Kang

“…The ML workflow comprised feature selection using the Boruta algorithm, model construction with seven classifiers, hyperparameter optimization via ten-fold cross-validation, model comparison based on the area under the curve (AUC), and a Shapley additive explanations (SHAP) analysis to analyze the significance of different features. 32.29% of patients showed inconsistency between AMR and MVO, but we successfully constructed a predictive model for MVO. …”
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