Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy by Miguel Angel Bergero, Pablo Martínez, Patricio Modina, Ricardo Hosman, Wenceslao Villamil, Romina Gudiño, Carlos David, Lucas Costa

“…This study aimed to develop a machine learning (ML) model to predict BCR in patients undergoing robot-assisted laparoscopic RP (RALP). …”
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High-Performance Deployment Operational Data Analytics of Pre-Trained Multi-Label Classification Architectures with Differential-Evolution-Based Hyperparameter Optimization (AutoDE... by Teo Prica, Aleš Zamuda

“…In this differential evolution (DE) optimization use case, we analyze how energy efficiently the DE algorithm performs with different DE strategies and ML models. …”
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Elemental augmentation of machine learning interatomic potentials by Haibo Xue, Guanjian Cheng, Wan-Jian Yin

“…In this work, we propose an elemental augmentation strategy to efficiently expand MLIPs by incorporating new elements into pre-trained models. Using a Bayesian optimization driven active learning framework, we target the configuration space of new elements where the current MLIPs exhibit high uncertainty and demonstrate the addition of up to 10 elements to a pre-trained UPot. …”
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Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

“…Taking these process parameters (<italic>x</italic>, <italic>y</italic>, <italic>z</italic>, <italic>d</italic>, <italic>h</italic>, <italic>n</italic>, <italic>a</italic>_p, <italic>a</italic>_e, <italic>f</italic>_z) as design variables, a multi-objective optimization model is constructed to balance machining efficiency and tool life. …”
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TQFLL: a novel unified analytics framework for translation quality framework for large language model and human translation of allusions in multilingual corpora by Li Yating, Muhammad Afzaal, Xiao Shanshan, Dina Abdel Salam El-Dakhs

“…The framework innovatively combines two automated evaluation metrics, BLEU and METEOR, with a translation quality assessment method derived from Fuzzy Mathematics and Optimality Theory. The findings of the study indicate that the GPT-3.5 translated version exhibits higher quality than the Volctrans version when evaluated by a machine. …”
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Reliable models for calculating the condensation heat transfer inside smooth helical tubes of different flow directions utilizing smart computational techniques by Chou-Yi Hsu, Nikunj Rachchh, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Ahmad Alkhayyat, Prabhat Kumar Sahu, Abhinav Kumar, Satvik Vats, F. Ranjbar

“…However, literature models are applicable only to specific operational and geometrical conditions. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…By integrating the predictive power of computational models and the data‐driven insights of AI, the synergy between these approaches has the potential to accelerate drug discovery, optimize treatment strategies, and usher in a new era of personalized medicine, benefiting patients, researchers, and the pharmaceutical industry as a whole.…”
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Decoding lake water eutrophication using an innovative dynamic model pool framework in Erhai Lake by Wei Si, Zhixiong Chen, Chi Yung Jim, Ngai Weng Chan, Mou Leong Tan, Bingbing Liu, Dong Liu, Lifei Wei, Shaoyong Wang, Fei Zhang

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A two-stage deep learning-based hybrid model for daily wind speed forecasting by Shahab S. Band, Rasoul Ameri, Sultan Noman Qasem, Saeid Mehdizadeh, Brij B. Gupta, Hao-Ting Pai, Danyal Shahmirzadi, Ely Salwana, Amir Mosavi

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Dynamic Multibody Modeling of Spherical Roller Bearings with Localized Defects for Large-Scale Rotating Machinery by Luca Giraudo, Luigi Gianpio Di Maggio, Lorenzo Giorio, Cristiana Delprete

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Development of a risk prediction model for secondary infection in severe/critical COVID-19 patients by Yinmei Zhang, Mingmei Lin, Zhenchao Wu, Zhongyu Han, Liyan Cui, Jiajia Zheng

“…The optimal model selected was further assessed, with model interpretability provided using SHapley Additive exPlanations (SHAP). …”
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Analysis of Electron Distribution Functions From the Magnetospheric Multiscale (MMS) Mission Using the Gaussian Mixture Model by Beniamino Sanò, Nathan N. Maes Anno, David L. Newman, Marty Goldman, Francesco Valentini, Denise Perrone, Giovanni Lapenta

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Analyzing the Application of Machine Learning in Anemia Prediction by Li Yuxi

“…This paper advocates for the systematic adoption of machine learning methodologies in anemia management, positing that such innovations are crucial for advancing public health and optimizing resource allocation in clinical settings.…”
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Temperature and Humidity Prediction Based on Machine Learning by Xiong Yanqi

“…This paper employs various machine learning models, including Linear Regression(LR). …”
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AI-powered model for predicting mortality risk in VA-ECMO patients: a multicenter cohort study by Shuai Wang, Sichen Tao, Ying Zhu, Qiao Gu, Peifeng Ni, Weidong Zhang, Chenxi Wu, Ruihan Zhao, Wei Hu, Mengyuan Diao

“…The model’s performance is evaluated using various statistical metrics and the optimal predictive model are identified. …”
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A Deep Learning Framework for Corrosion Assessment of Steel Structures Using Inception v3 Model by Xinghong Huang, Zhen Duan, Shaojin Hao, Jia Hou, Wei Chen, Lixiong Cai

“…A comparative evaluation with other architectures, namely, AlexNet, ResNet, and VggNet, demonstrated that the Inception v3 model achieved superior classification accuracy, exceeding 95%. …”
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PLM-ATG: Identification of Autophagy Proteins by Integrating Protein Language Model Embeddings with PSSM-Based Features by Yangying Wang, Chunhua Wang

“…Third, we selected the optimal feature subset from the combination of the ESM-2 embeddings and AADP-PSSM features to train the final SVM model. …”
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Classification of Mycena and <i>Marasmius</i> Species Using Deep Learning Models: An Ecological and Taxonomic Approach by Fatih Ekinci, Guney Ugurlu, Giray Sercan Ozcan, Koray Acici, Tunc Asuroglu, Eda Kumru, Mehmet Serdar Guzel, Ilgaz Akata

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Advancing ADMET prediction for major CYP450 isoforms: graph-based models, limitations, and future directions by Asmaa A. Abdelwahab, Mustafa A. Elattar, Sahar Ali Fawzi

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Modeling the unconfined compressive strength of lateritic soil treated with FGD gypsum as a partial cement replacement by Chidananda M Linganagoudar, Shiva Kumar G, M S Ujwal, G Rohith, A Vinay, Poornachandra Pandit

“…To support predictive insights, machine learning models including Decision Tree, Random Forest, and Multi-Layer Perceptron (MLP) were trained on 168 data samples. …”
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