Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence by Jan-Niklas Eckardt, Waldemar Hahn, Christoph Röllig, Sebastian Stasik, Uwe Platzbecker, Carsten Müller-Tidow, Hubert Serve, Claudia D. Baldus, Christoph Schliemann, Kerstin Schäfer-Eckart, Maher Hanoun, Martin Kaufmann, Andreas Burchert, Christian Thiede, Johannes Schetelig, Martin Sedlmayr, Martin Bornhäuser, Markus Wolfien, Jan Moritz Middeke

“…We employed two different methodologies of generative artificial intelligence – CTAB-GAN+ and normalizing flows (NFlow) – to synthesize patient data derived from 1606 patients with acute myeloid leukemia, a heterogeneous hematological malignancy, that were treated within four multicenter clinical trials. Both generative models accurately captured distributions of demographic, laboratory, molecular and cytogenetic variables, as well as patient outcomes yielding high performance scores regarding fidelity and usability of both synthetic cohorts (n = 1606 each). …”
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Earth Dam Design for Drinking Water Management and Flood Control: A Case Study by Bethy Merchán-Sanmartín, Joselyn Aucapeña-Parrales, Ricardo Alcívar-Redrován, Paúl Carrión-Mero, María Jaya-Montalvo, Mijail Arias-Hidalgo

“…The design includes a waterproofing system that controls possible leaks and a cymbal spillway, mainly for raw water collection. The generated model showed that the shorter the failure time, the higher the maximum output flow. …”
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Stochastic Modeling for Estimating Real-Time Inundation Depths at Roadside IoT Sensors Using the ANN-Derived Model by Shiang-Jen Wu, Chih-Tsu Hsu, Che-Hao Chang

“…To enhance the reliability and accuracy of the proposed SM_EID_IOT model in the estimations of the inundation depths at the IoT sensors, a great number of the rainfall induced flood events as the training and validation datasets are simulated by the 2D hydraulic dynamic (SOBEK) model with the simulated rain fields via the stochastic generation model for the short-term gridded rainstorms. …”
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Research on Coal and Gas Outburst Risk Warning Based on Multiple Algorithm Fusion by Yanlei Guo, Haibin Liu, Xu Zhou, Jian Chen, Liwen Guo

“…The statistic is based on gas outburst data from 26 mines and establishes a data generation model based on XGBoost. The obtained virtual datasets are analyzed through visualization analysis and ROC curve analysis with respect to the original data. …”
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Comparative utilization of drone technology vs. traditional methods in open pit stockpile volumetric computation: A case of njuli quarry, Malawi by Jabulani Matsimbe, Jabulani Matsimbe, Jabulani Matsimbe, Wisdom Mdolo, Charles Kapachika, Innocent Musonda, Megersa Dinka

“…Findings show that the smaller the error of the checkpoints the more accurate the generated model making the measurements reliable. The generated Pix4D quality report showed a root mean square error of 0.019. …”
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Efficient Network Architecture Search Using Hybrid Optimizer by Ting-Ting Wang, Shu-Chuan Chu, Chia-Cheng Hu, Han-Dong Jia, Jeng-Shyang Pan

“…Therefore, we propose a novel deep architecture generation model based on Aquila optimization (AO) and a genetic algorithm (GA). …”
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Evolution Characteristics of Landscape Patterns and the Response of Surface Runoff in a Rapid Urbanization Area: Focus on the Chang–Zhu–Tan Metropolitan Area of China by Tang Li, Cunyou Chen, Qizhen Li, Luyun Liu, Zhiyuan Wang, Xijun Hu, Saroj Thapa

“…The influence of landscape pattern evolution on surface runoff was studied using the SCS-CN flow generation model, the moving window method, and Pearson’s analysis. …”
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Deployment of Model-Based-Design-Adaptive Controllers for Monitoring and Control Mechatronic Devices by Ramon Barber, David R. Rosa, Antonio Flores-Caballero, Santiago Garrido

“…They are carried out in the prototyping phase with engineering software development tools, generating models, and control algorithms that are not always easily exportable to control hardware. …”
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AI/ML combined with next-generation sequencing of VHH immune repertoires enables the rapid identification of de novo humanized and sequence-optimized single domain antibodies: a pr... by Paul Arras, Paul Arras, Han Byul Yoo, Lukas Pekar, Thomas Clarke, Lukas Friedrich, Christian Schröter, Jennifer Schanz, Jason Tonillo, Vanessa Siegmund, Achim Doerner, Simon Krah, Enrico Guarnera, Stefan Zielonka, Stefan Zielonka, Andreas Evers

“…For each cluster, long short-term memory (LSTM) based deep generative models were trained and used for the in silico sampling of new sequences. …”
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Thermal Dynamic Exploration of Full-Ceramic Ball Bearings under the Self-Lubrication Condition by Junxing Tian, Yuhou Wu, Jian Sun, Zhongxian Xia, Kexuan Ren, He Wang, Songhua Li, Jinmei Yao

“…The bearing heat generation model based on the silicon nitride material coefficient is established, and the life test machine measures the temperature of the bearing to verify the accuracy of the simulation model. …”
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Non-Linearity in Motor Unit Velocity Twitch Dynamics: Implications for Ultrafast Ultrasound Source Separation by Emma Lubel, Bruno Grandi Sgambato, Robin Rohlen, Jaime Ibanez, Deren Y. Barsakcioglu, Meng-Xing Tang, Dario Farina

“…This observation indicates non-linear factors in the generation model. Furthermore, we directly studied the impact of one MU on a neighboring MU, finding that the effect of one source on the other is not symmetrical and may be related to unit size. …”
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DeepFake on Face and Expression Swap: A Review by Saima Waseem, Syed Abdul Rahman Syed Abu Bakar, Bilal Ashfaq Ahmed, Zaid Omar, Taiseer Abdalla Elfadil Eisa, Mhassen Elnour Elneel Dalam

“…Remarkable advances have been made in deep learning, leading to the emergence of highly realistic AI-generated videos known as deepfakes. Deepfakes use generative models to manipulate facial features to create modified identities or expressions with impressive realism. …”
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SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan by Isma Kulsoom, Weihua Hua, Sadaqat Hussain, Qihao Chen, Garee Khan, Dai Shihao

“…The deformation of generated models in susceptible regions was evaluated using SBAS-InSAR (Small-Baseline subset-Interferometric Synthetic Aperture Radar) technique. …”
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osl-dynamics, a toolbox for modeling fast dynamic brain activity by Chetan Gohil, Rukuang Huang, Evan Roberts, Mats WJ van Es, Andrew J Quinn, Diego Vidaurre, Mark W Woolrich

“…At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. …”
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GPR Detection of Fossil Structures in Conductive Media Supported by FDTD Modelling and Attributes Analysis: An Example from Early Pleistocene Marine Clay at Bargiano Site (Central... by Maurizio Ercoli, Roberto Bizzarri, Angela Baldanza, Angela Bertinelli, Diego Mercantili, Cristina Pauselli

“…The study site is characterized by a very uneven topography shaping highly conductive clayey deposits, representing not exactly ideal conditions for GPR surveying. After generating models encompassing a real topography and variable electrical properties of media, we simulated buried fossil structures at variable depth with different size and geometry, using different operative frequencies. …”
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A Feasibility Study on Gravity Power Generation Technology by Virtue of Abandoned Oil-Gas Wells in China by Jingcui Li, Jifang Wan, Yan Xia, Sixiang Zhao, Guowei Song, Yuxian He

“…In this study, a scheme of gravity power generation by virtue of the spud-in casing depth of oil-gas wells is proposed, and a gravity power generation model based on abandoned oil-gas wells is established. …”
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Comparison of learning models to predict LDPE, PET, and ABS concentrations in beach sediment based on spectral reflectance by Faisal Raiyan Huda, Florina Stephanie Richard, Ishraq Rahman, Saeid Moradi, Clarence Tay Yuen Hua, Christabel Anfield Sim Wanwen, Ting Lik Fong, Aazani Mujahid, Moritz Müller

“…Both approaches generated models of good accuracy with R2 values greater than 0.7, root mean squared error (RMSE) values less than 3 and mean absolute error (MAE) < 2.2. …”
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QSAR studies on some C14-urea tetrandrine compounds as potent anti-cancer against Leukemia cell line (K562) by Abdullahi Mustapha, Gideon Shallangwa, Muhammad Tukur Ibrahim, Abdullahi Umar Bello, David Arthur Ebuka, Adamu Uzairu, Paul Mamza

“…The coefficient of determination (𝑐𝑅2𝑝) parameter was calculated as 0.819296 which is greater than 0.5, this affirms that the generated model is robust. Furthermore, AST4p, GATS8v and MLFER are the descriptors in the model with positive mean effect of 0.089972855, 0.909814859 and 0.000212286 respectively. …”
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A basic approach to the verification and validation of sorption isotherm models by Lutovska Monika, Pavkov Ivan, Mijakovski Vladimir, Stamenkovič Zoran

“…The success of the newly generated model was confirmed in relation to this reference model.…”
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Physicomechanical Behavior of High-Performance Concrete Reinforced with Recycled Steel Fibers from Twisted Cables in the Brittle State—Experimentation and Statistics by Yazid Chetbani, Rebih Zaitri, Bassam A. Tayeh, Ibrahim Y. Hakeem, Fodil Dif, Yasmina Kellouche

“…The accuracy and validation of the generated models were evaluated by employing analysis of variance (ANOVA) and optimal parameters. …”
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