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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
algorithm body » algorithm both (Expand Search), algorithm model (Expand Search), algorithm blood (Expand Search)
algorithm api » algorithm ai (Expand Search), algorithm a (Expand Search), algorithm i (Expand Search)
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241
Landscape17
Published 2025“…</p><p dir="ltr">We utilized TopSearch, an open-source Python package, to perform landscape exploration, at an estimated cost of 10<sup>5 </sup>CPUh. …”
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242
<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b>
Published 2025“…</p><h2>Project Structure</h2><pre><pre>Perception_based_neighbourhoods/<br>├── raw_data/<br>│ ├── ET_cells_glasgow/ # Glasgow grid cells for analysis<br>│ └── glasgow_open_built/ # Built area boundaries<br>├── svi_module/ # Street View Image processing<br>│ ├── svi_data/<br>│ │ ├── svi_info.csv # Image metadata (output)<br>│ │ └── images/ # Downloaded images (output)<br>│ ├── get_svi_data.py # Download street view images<br>│ └── trueskill_score.py # Generate TrueSkill scores<br>├── perception_module/ # Perception prediction<br>│ ├── output_data/<br>│ │ └── glasgow_perception.nc # Perception scores (demo data)<br>│ ├── trained_models/ # Pre-trained models<br>│ ├── pred.py # Predict perceptions from images<br>│ └── readme.md # Training instructions<br>└── cluster_module/ # Neighbourhood clustering<br> ├── output_data/<br> │ └── clusters.shp # Final neighbourhood boundaries<br> └── cluster_perceptions.py # Clustering algorithm<br></pre></pre><h2>Prerequisites</h2><ul><li>Python 3.8 or higher</li><li>GDAL/OGR libraries (for geospatial processing)</li></ul><h2>Installation</h2><ol><li>Clone this repository:</li></ol><p dir="ltr">Download the zip file</p><pre><pre>cd perception_based_neighbourhoods<br></pre></pre><ol><li>Install required dependencies:</li></ol><pre><pre>pip install -r requirements.txt<br></pre></pre><p dir="ltr">Required libraries include:</p><ul><li>geopandas</li><li>pandas</li><li>numpy</li><li>xarray</li><li>scikit-learn</li><li>matplotlib</li><li>torch (PyTorch)</li><li>efficientnet-pytorch</li></ul><h2>Usage Guide</h2><h3>Step 1: Download Street View Images</h3><p dir="ltr">Download street view images based on the Glasgow grid sampling locations.…”
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243
Image2_A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddlers.pd...
Published 2024“…PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. …”
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244
Image1_A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddlers.pd...
Published 2024“…PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. …”
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245
Table3_A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddlers.xl...
Published 2024“…PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. …”
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246
Image4_A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddlers.pd...
Published 2024“…PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. …”
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247
Datasheet1_A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddler...
Published 2024“…PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. …”
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248
Image3_A young child formula supplemented with a synbiotic mixture of scGOS/lcFOS and Bifidobacterium breve M-16V improves the gut microbiota and iron status in healthy toddlers.pd...
Published 2024“…PICRUSt, a predictive functionality algorithm based on 16S ribosomal gene sequencing, was used to correlate potential microbial functions with iron status measurements. …”
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249
MCCN Case Study 2 - Spatial projection via modelled data
Published 2025“…This study demonstrates: 1) Description of spatial assets using STAC, 2) Loading heterogeneous data sources into a cube, 3) Spatial projection in xarray using different algorithms offered by the <a href="https://pypi.org/project/PyKrige/" rel="nofollow" target="_blank">pykrige</a> and <a href="https://pypi.org/project/rioxarray/" rel="nofollow" target="_blank">rioxarray</a> packages.…”
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250
Data Sheet 1_Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy.pdf
Published 2025“…Eleven ML algorithms were trained and validated using Python, and external validation and performance evaluations were conducted. …”
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251
Table 2_Harnessing serum VOCs and machine learning for the early detection of MAFLD.xlsx
Published 2025“…Clinical and biochemical parameters such as age, body mass index, liver function, and lipid profiles were also compared between groups.…”
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252
Image 2_Harnessing serum VOCs and machine learning for the early detection of MAFLD.jpeg
Published 2025“…Clinical and biochemical parameters such as age, body mass index, liver function, and lipid profiles were also compared between groups.…”
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253
Image 1_Harnessing serum VOCs and machine learning for the early detection of MAFLD.jpeg
Published 2025“…Clinical and biochemical parameters such as age, body mass index, liver function, and lipid profiles were also compared between groups.…”
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254
Table 1_Harnessing serum VOCs and machine learning for the early detection of MAFLD.xlsx
Published 2025“…Clinical and biochemical parameters such as age, body mass index, liver function, and lipid profiles were also compared between groups.…”
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255
Table 1_Trajectories of health conditions predict cardiovascular disease risk among middle-aged and older adults: a national cohort study.docx
Published 2025“…Trajectories of multimorbidity status, activities of daily living (ADLs) limitations, body roundness index (BRI), pain, sleep duration, depressive symptoms, and cognitive function were identified using latent class growth models (LCGMs). …”
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256
Assessing the risk of acute kidney injury associated with a four-drug regimen for heart failure: a ten-year real-world pharmacovigilance analysis based on FAERS events
Published 2025“…Disproportionality analysis and subgroup analysis were performed using four algorithms. Time-to-onset (TTO) analysis was used to assess the temporal risk patterns of ADE occurrence. …”
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257
AP-2α 相关研究
Published 2025“…</p><p dir="ltr"><b>Figure 4 | Comparative transcriptomic analysis of the functional regulation of </b><b><i>VdAP-2α</i></b><b> in </b><b><i>Verticillium dahliae.…”