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python model » python tool (Expand Search), action model (Expand Search), motion model (Expand Search)
new implementation » _ implementation (Expand Search), model implementation (Expand Search), after implementation (Expand Search)
python model » python tool (Expand Search), action model (Expand Search), motion model (Expand Search)
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261
Concurrent spin squeezing and field tracking with machine learning
Published 2025“…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”
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262
Soulware-Lite
Published 2025“…It supports OpenAI GPT-4, Anthropic Claude, Google Gemini, Meta LLaMA, and other open-source models.</p><p><br></p><p dir="ltr">Soulware-Lite is the first live implementation of a cognitive conscience layer, born from architectural failures in AI output hallucination and anchored by integrity principles like MAP/ARP and RDIP. …”
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263
Table 3_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
Published 2025“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
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264
Table 2_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
Published 2025“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
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265
Table 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
Published 2025“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
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266
Data Sheet 1_Novel deep learning-based prediction of HER2 expression in breast cancer using multimodal MRI, nomogram, and decision curve analysis.docx
Published 2025“…Nomogram construction, ROC analysis, and DCA evaluation were performed to assess model performance. Statistical analyses were conducted using Python and R, with significance set at p < 0.05.…”
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267
Folder with all data and algorithms
Published 2025“…In this study, we present an open-source, Python-based computational framework that unifies photon transport modeling, probe geometry optimization, and photothermal safety assessment into a single workflow. …”
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268
Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025
Published 2025“…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…”
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269
MSc Personalised Medicine at Ulster University
Published 2025“…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…”
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270
Gene Editing using Transformer Architecture
Published 2025“…., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”
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271
Summary of Tourism Dataset.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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272
Segment-wise Spending Analysis.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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273
Hyperparameter Parameter Setting.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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274
Marketing Campaign Analysis.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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275
Visitor Segmentation Validation Accuracy.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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276
Integration of VAE and RNN Architecture.
Published 2025“…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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277
Investigating the far-right online: Using text data to understand online subcultures
Published 2025“…While these analytical techniques are new, they are actually fairly easy for social researchers to implement due to the nature of contemporary high-level programming languages such as Python.…”
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278
Table 1_Analysis of distribution equilibrium and influencing factors for older adult meal service facilities in mainland China.xlsx
Published 2025“…A multiple linear regression model was applied to explore the relationships between older adult meal services and factors such as population, economy, infrastructure, geography, and policies.…”
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279
Core-Based Smart Sampling Framework: A Theoretical and Experimental Study on Randomized Partitioning for SAT Problems
Published 2025“…We provide theoretical guarantees on complexity reduction and probabilistic completeness, apply the method to SAT instances, and evaluate its performance using experimental Python implementations. The results show that smart sampling drastically reduces the effective complexity of SAT problems and offers new insights into the structure of NP-complete problems.…”
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280
Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2)
Published 2025“…Full source code and version details are available upon request.…”