WisdomModel: convert data into wisdom by Israa Mahmood, Hasanen Abdullah

“…Findings – The authors have evaluated the WisdomModel using different measures such as accuracy, recall, precision, f-measure, receiver operating characteristics (ROC) curve, area under the curve (AUC) and error rate with various data sets to prove its ability to generalize without human involvement. …”
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Prediction of success in assisted reproductive technology with the help of morphology of the testis by N. G. Kulchenko

“…The results of morphological studies in these men showed a different degree of violation of spermatogenesis. Based on the study, a diagnostic algorithm of patients with male infertility is proposed, which allows to predict the success of ART taking into account morphological changes in the testicle.Conclusion. …”
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Hybrid adaptive method for lane detection of degraded road surface condition by Khaled H. Almotairi

“…Subsequently, numerical features about the boundaries of the candidate lanes are extracted and used by a model of the k-nearest neighbor algorithm and the Gaussian process for final lane discovery. …”
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DRL-based Joint Beamforming and Power Allocation in Beyond Diagonal Reconfigurable Intelligence Surface 6G Systems by Mousa Abdollahvand, Sima Sobhi-givi

“…Additionally, we analyze the convergence speed and performance trade-offs of different DRL algorithms, emphasizing the importance of selecting the appropriate algorithm and hyper-parameters for specific applications. …”
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Optimizing decentralized implementation of state estimation in active distribution networks by Mohammad Gholami, Aref Eskandari, Sajjad Fattaheian‐Dehkordi, Matti Lehtonen

“…For this purpose, initially, an algorithm is used to partition the network into all possible configurations with different sizes. …”
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Single image de-raining by multi-scale Fourier Transform network. by Chaobing Zheng, Yao Yao, Wenjian Ying, Shiqian Wu

“…Finally, a multi-scale neural network incorporating attention mechanisms at different scales is applied to further refine the processed features, enhancing the robustness of the algorithm. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…Then, the most predictive radiomic features were selected and their corresponding coefficients were evaluated using the correlation coefficient algorithm and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. …”
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Predicting the infecting dengue serotype from antibody titre data using machine learning. by Bethan Cracknell Daniels, Darunee Buddhari, Taweewun Hunsawong, Sopon Iamsirithaworn, Aaron R Farmer, Derek A T Cummings, Kathryn B Anderson, Ilaria Dorigatti

“…Despite these challenges, the best performing machine learning algorithm achieved 76.3% (95% CI 57.9-89.5%) accuracy on the out-of-sample test set in predicting the infecting serotype from PRNT data. …”
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Are Suggested Hiking Times Accurate? A Validation of Hiking Time Estimations for Preventive Measures in Mountains by Marco Vecchiato, Nicola Borasio, Emiliano Scettri, Vanessa Franzoi, Federica Duregon, Sandro Savino, Andrea Ermolao, Daniel Neunhaeuserer

“…Traditional mountain signage and online platforms provide generalized hiking time recommendations, often lacking personalization. This study aims to evaluate the variability in hiking time estimates from different methods and assess the potential of a novel algorithm, MOVE, to enhance accuracy and safety. …”
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An analysis of the relationship of triglyceride glucose index with diffuse large B-cell lymphoma prognosis: a retrospective study by QingQing Luo, Zhixiang Lei, Haizhou Miao, Ting Huang, Li Yu

“…Subgroup analyses were conducted to assess the prognostic value of the TyG index across different patient subgroups. Finally, a nomogram model based on the TyG index was developed, and its predictive performance was evaluated using the area under the receiver operating characteristic curve (AUROC), calibration curves, and decision curve analysis (DCA).ResultsA total of 186 DLBCL patients were included in this study. …”
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Fully-automated segmentation of muscle and inter-/intra-muscular fat from magnetic resonance images of calves and thighs: an open-source workflow in Python by Kenneth Tam, Si Wen Liu, Sarah Costa, Eva Szabo, Shannon Reitsma, Hana Gillick, Jonathan D. Adachi, Andy Kin On Wong

“…Robustness and versatility of the algorithm was demonstrated by application to different MR sequences/magnetic strength and to calf versus thigh scans. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…In this paper, the exhaustive feature selection algorithm is employed to assess every possible combination of features in a dataset to evaluate its performance. …”
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Interannual changes of carbon storage in mangrove forests in Futian based on WorldView-3 remote sensing images by HU Liuliu1, TAN Min2, LUO Qin2, HUANG Zijian2, XIANG Xuelian2, LI Buhang2, YU Shixiao2, WU Zefeng1, YANG Qiong1, HU Ping1*

“…These results provide foundational data for evaluating the carbon sequestration capacities of different dominant communities in Futian mangrove, in tandem with scientific support for subsequent mangrove restoration and management.…”
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Does machine learning outperform logistic regression in predicting individual tree mortality? by Aitor Vázquez-Veloso, Astor Toraño Caicoya, Felipe Bravo, Peter Biber, Enno Uhl, Hans Pretzsch

“…Here, we compare the performance of five different ML algorithms (Decision Trees, Random Forest, Naive Bayes, K-Nearest Neighbour, and Support Vector Machine) against Logistic binomial Regression in individual tree mortality classification under 40 different case studies and a cross-validation case study. …”
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Genome-wide identification and expression profile analysis of the NAC transcription factor family during abiotic and biotic stress in woodland strawberry. by He Zhang, Hao Kang, Chulian Su, Yanxiang Qi, Xiaomei Liu, Jinji Pu

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Sensorless real-time solar irradiance prediction in grid-connected PV systems using PSO-MPPT and IoT-enabled monitoring by Ali Zaki Mohammed Nafa, Adel A. Obed, Ahmed J. Abid, Salam J. Yaqoob, Mohit Bajaj, Mohammad Shabaz

“…As well as to represent realistic PV operating conditions of 15 °C for low cell temperature, 45 °C as the nominal operating cell temperature (NOCT), and 65 °C for high cell temperature, enabling performance evaluation across a practical temperature range. Each irradiance level was applied for 7.5 s to evaluate the PSO’s tracking capability under dynamic conditions. …”
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Subgrouping suicidal ideations: an ecological momentary assessment study in psychiatric inpatients by Stephanie Homan, Zachary Roman, Anja Ries, Prabhakaran Santhanam, Sofia Michel, Anna-Marie Bertram, Nina Klee, Carlo Berther, Sarina Blaser, Marion Gabi, Philipp Homan, Hanne Scheerer, Michael Colla, Stefan Vetter, Sebastian Olbrich, Erich Seifritz, Isaac Galatzer-Levy, Tobias Kowatsch, Urte Scholz, Birgit Kleim

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Rhodanine derivatives as potent anti-HIV and anti-HSV microbicides. by Cristina Tintori, Giulia Iovenitti, Elisa Rita Ceresola, Roberto Ferrarese, Claudio Zamperini, Annalaura Brai, Giulio Poli, Elena Dreassi, Valeria Cagno, David Lembo, Filippo Canducci, Maurizio Botta

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Biomarkers of microvascularture by ultra Micro-angiography (UMA) assist to identify papillary thyroid carcinoma (PTC) with atypia of undetermined significance by Qingsong Wang, Zhewei Li, Jie Zhang, Sijie Zhang, Lijun Wang, Hongjian Yao, Hong Zhang, Jing Li, Shuo Wang, Jinglai Sun, Wenhui Zhang, Hui Yu

“…Moreover, the morphology of microvasculature showed different changes at different LD groups.…”
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Shared pathogenesis in polycystic ovaries and rheumatoid arthritis: an analysis of key genes and pathways by Yingying Ji, Pengcheng Xia, Yan Wang, Yang Liu, Feng Wang, Fenggang Sun, Qiang Feng, Qingbin Ni, Yi Li

“…Gene Ontology (GO) and KEGG pathway enrichment analyses were performed to understand the biological processes and pathways associated with the differentially expressed genes (DEGs). Protein interaction analysis, machine learning algorithms, and validation analyses were employed to identify core genes with potential diagnostic value. …”
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