machine learning assisted integrated data-driven framework Search Results


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AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by <t>machine</t> <t>learning.</t> Copyright 2023, <t>Cell</t> press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].
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AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by <t>machine</t> <t>learning.</t> Copyright 2023, <t>Cell</t> press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].
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AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by <t>machine</t> <t>learning.</t> Copyright 2023, <t>Cell</t> press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].
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AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by <t>machine</t> <t>learning.</t> Copyright 2023, <t>Cell</t> press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].
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AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by <t>machine</t> <t>learning.</t> Copyright 2023, <t>Cell</t> press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].
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JEOL jem-f200 transmission electron microscope
AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by <t>machine</t> <t>learning.</t> Copyright 2023, <t>Cell</t> press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].
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Image Search Results


AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by machine learning. Copyright 2023, Cell press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].

Journal: Bioactive Materials

Article Title: Harnessing the power of artificial intelligence for human living organoid research

doi: 10.1016/j.bioactmat.2024.08.027

Figure Lengend Snippet: AI-guided optimization of the LO culture system. (A) Optimization and fabrication of alginate bioblocks with tunable morphology, rheological and injectable characteristics by machine learning. Copyright 2023, Cell press. (B) Deep learning for cancer immunotherapy screening. Copyright 2022, PNAS. (C) Characterizing stem cell-derived organoids from electrical signals with machine learning. Copyright 2019, IEEE [ , , ].

Article Snippet: Copyright 2021, The Company of Biologists Ltd. (C) Data-driven cell segmentation-free machine learning recorded the phenotypic responses of dense cortical neurons to pharmacological inhibition of anti-apoptotic proteins.

Techniques: Derivative Assay

AI accelerated the data extraction and analysis of LOs. (A) A new deep neural network was developed to dynamically capture and track trajectories of organoids over time during culture based on the dataset of high-throughput organoid images. Copyright 2021, Elsevier Ltd. (B) Data-driven feature learning has the ability to classify, cluster and visualize 3D images, as well as rapidly quantitative phenotyping analysis of LOs. Copyright 2021, The Company of Biologists Ltd. (C) Data-driven cell segmentation-free machine learning recorded the phenotypic responses of dense cortical neurons to pharmacological inhibition of anti-apoptotic proteins. Copyright 2021, PLoS [ , , ].

Journal: Bioactive Materials

Article Title: Harnessing the power of artificial intelligence for human living organoid research

doi: 10.1016/j.bioactmat.2024.08.027

Figure Lengend Snippet: AI accelerated the data extraction and analysis of LOs. (A) A new deep neural network was developed to dynamically capture and track trajectories of organoids over time during culture based on the dataset of high-throughput organoid images. Copyright 2021, Elsevier Ltd. (B) Data-driven feature learning has the ability to classify, cluster and visualize 3D images, as well as rapidly quantitative phenotyping analysis of LOs. Copyright 2021, The Company of Biologists Ltd. (C) Data-driven cell segmentation-free machine learning recorded the phenotypic responses of dense cortical neurons to pharmacological inhibition of anti-apoptotic proteins. Copyright 2021, PLoS [ , , ].

Article Snippet: Copyright 2021, The Company of Biologists Ltd. (C) Data-driven cell segmentation-free machine learning recorded the phenotypic responses of dense cortical neurons to pharmacological inhibition of anti-apoptotic proteins.

Techniques: Extraction, High Throughput Screening Assay, Inhibition

A summary of the preclinical applications of AI-enabled LO research.

Journal: Bioactive Materials

Article Title: Harnessing the power of artificial intelligence for human living organoid research

doi: 10.1016/j.bioactmat.2024.08.027

Figure Lengend Snippet: A summary of the preclinical applications of AI-enabled LO research.

Article Snippet: Copyright 2021, The Company of Biologists Ltd. (C) Data-driven cell segmentation-free machine learning recorded the phenotypic responses of dense cortical neurons to pharmacological inhibition of anti-apoptotic proteins.

Techniques: In Vivo, Transplantation Assay, Activity Assay