Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharma... by Auwal Salisu Isa, Adamu Uzairu, Umar Mele Umar, Muhammad Tukur Ibrahim, David Ebuka Arthur, Samuel Ndaghiya Adawara

“…The present research was centered on the development of a predictive model aimed at assessing the responses of prostate tumors to a range of compounds within the scope of the pIC50 project. …”
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Analysing and Forecasting the Energy Consumption of Healthcare Facilities in the Short and Medium Term. A Case Study by Ali Koç, Serap Ulusam Seçkiner

“…Furthermore, all regression algorithms have undergone hyper-parameter optimisation using random search, grid search and Bayesian optimisation to achieve the minimum prediction errors represented by different metrics. …”
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Pandemic velocity: Forecasting COVID-19 in the US with a machine learning & Bayesian time series compartmental model. by Gregory L Watson, Di Xiong, Lu Zhang, Joseph A Zoller, John Shamshoian, Phillip Sundin, Teresa Bufford, Anne W Rimoin, Marc A Suchard, Christina M Ramirez

“…We embed a Bayesian time series model and a random forest algorithm within an epidemiological compartmental model for empirically grounded COVID-19 predictions. …”
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Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling. by Biche Osong, Eric Sribnick, Jonathan Groner, Rachel Stanley, Lauren Schulz, Bo Lu, Lawrence Cook, Henry Xiang

“…Data were split into two sets, where 80% developed a decision tree, and 20% tested predictive performance. We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots.…”
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Preoperative assessment of tertiary lymphoid structures in stage I lung adenocarcinoma using CT radiomics: a multicenter retrospective cohort study by Xiaojiang Zhao, Yuhang Wang, Mengli Xue, Yun Ding, Han Zhang, Kai Wang, Jie Ren, Xin Li, Meilin Xu, Jun Lv, Zixiao Wang, Daqiang Sun

“…Tumor segmentation was achieved using an automatic virtual adversarial training segmentation algorithm based on a three-dimensional U-shape convolutional neural network (3D U-Net). …”
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The association between inflammatory, metabolic, and hepatic fibrosis-related biomarkers and atrial fibrillation in older patients with metabolic dysfunction-associated steatotic l... by Shuai Zhang, Hao Liang, Jun Liu, Zhipeng Huang, Xijing Shi, Ye Zhu

“…The variable importance ranking results based on the Boruta algorithm, as well as the Receiver Operating Characteristic (ROC) curve and Decision Curve Analysis (DCA), all indicate that NFS and ALBI have high predictive performance and clinical benefits. …”
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Aspects of Developing A Methodology for Managing Digital Financial Assets by A. Yu. Proskuryakov

“…The subject of the study is methods, models and algorithms for automated monitoring and management of digital financial assets and cryptocurrencies. …”
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Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data. …”
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MRI-based brain tumor ensemble classification using two stage score level fusion and CNN models by Oussama Bouguerra, Bilal Attallah, Youcef Brik

“…In the second stage, ensemble learning algorithms like weighted sum, fuzzy rank, and majority vote are used to combine the scores from the trained models, enhancing prediction results. …”
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Development experience of information system for ranking of academic and pedagogical staff by A. A. Chernousov, E. V. Vavilova

“…The aim of this work is research of algorithms for quantitative assessment of intellectual potential (rating) of academic and pedagogical staff in higher educational institutions, as well as the development of technology for the application of these algorithms in practice.Materials and methods. …”
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Preface to Special Issue on AI-Based Future Intelligent Networks and Communication Security by Sunil Kumar, Glenford Mapp, Abhay Bansal, Korhan Cengiz

“… Recent advancements in science focus on the study and development of algorithms that can learn from and make predictions and decisions based on data collected through intelligent devices. …”
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Identification of biomarkers associated with inflammatory response in Parkinson's disease by bioinformatics and machine learning. by Yatan Li, Wei Jia, Chen Chen, Cheng Chen, Jinchao Chen, Xinling Yang, Pei Liu

“…LASSO, SVM-RFE and Random Forest algorithms were used to screen biomarker genes. Then, ROC curves were drawn and PD risk predicting models were constructed on the basis of the biomarker genes. …”
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Transforming tabular data into images via enhanced spatial relationships for CNN processing by Hameedah A. Alenizy, Jawad Berri

“…The results showed that NCTD consistently surpassed the majority of competing algorithms in nine out of ten datasets, indicating its potential as a robust tool for extending CNN applicability beyond conventional image-based domains, particularly in complex classification and prediction.…”
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Machine Learning Ensemble Classifiers for Feature Selection in Rice Cultivars by Chandrakumar Thangavel, D Sakthipriya

“…Machine Learning is crucial for seed prediction, germination, crop production, soil moisture, and land suitability evaluation. …”
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Efficient topology control for time-varying spacecraft networks with unreliable links by Wei Zhang, Hong Ma, Tao Wu, Xueshu Shi, Yiwen Jiao

“…Simulation results demonstrate the efficiency of our model and topology control algorithms.…”
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A novel deep learning approach to identify embryo morphokinetics in multiple time lapse systems by Guillaume Canat, Antonin Duval, Nina Gidel-Dissler, Alexandra Boussommier-Calleja

“…Today, most of the literature has characterized algorithms that predict pregnancy, ploidy or blastocyst quality, leaving to the side the task of identifying key morphokinetic events. …”
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Deep reinforcement learning for inverse inorganic materials design by Christopher Karpovich, Elton Pan, Elsa A. Olivetti

“…We apply template-based crystal structure prediction to suggest feasible crystal structure matches for target inorganic compositions identified by our machine learning (ML) algorithms to highlight the plausibility of the identified target compositions. …”
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A machine learning‐based approach for wait‐time estimation in healthcare facilities with multi‐stage queues by Amjed Al‐Mousa, Hamza Al‐Zubaidi, Mohammad Al‐Dweik

“…The work employs feature engineering and compares several machine learning‐based algorithms to predict patients' waiting times for single‐stage and multi‐stage services. …”
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Fuzzy AHP Based Optimal Design Building-Attached Photovoltaic System for Academic Campus by Mega Ardisa Hapsari, Subiyanto Subiyanto

“…Several algorithms have been developed for building-attached photovoltaic system (BAPV) planning in educational institute based on PV capacity. …”
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Efficient search, mapping, and optimization of multi‐protein genetic systems in diverse bacteria by Iman Farasat, Manish Kushwaha, Jason Collens, Michael Easterbrook, Matthew Guido, Howard M Salis

“…We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram‐positive and gram‐negative bacterial hosts. …”
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