Revolutionizing Prostate Cancer Therapy: Artificial intelligence – based Nanocarriers for Precision Diagnosis and Treatment

Critical Reviews in Oncology/Hematology, Journal Year: 2025, Volume and Issue: unknown, P. 104653 - 104653

Published: Feb. 1, 2025

Language: Английский

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Evaluating batch correction methods for image-based cell profiling

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Aug. 2, 2024

Abstract High-throughput image-based profiling platforms are powerful technologies capable of collecting data from billions cells exposed to thousands perturbations in a time- and cost-effective manner. Therefore, has been increasingly used for diverse biological applications, such as predicting drug mechanism action or gene function. However, batch effects severely limit community-wide efforts integrate interpret collected across different laboratories equipment. To address this problem, we benchmark ten high-performing single-cell RNA sequencing (scRNA-seq) correction techniques, representing approaches, using newly released Cell Painting dataset, JUMP. We focus on five scenarios with varying complexity, ranging batches prepared single lab over time imaged microscopes multiple labs. find that Harmony Seurat RPCA noteworthy, consistently ranking among the top three methods all tested while maintaining computational efficiency. Our proposed framework, benchmark, metrics can be assess new future. This work paves way improvements enable community make best use public scientific discovery.

Language: Английский

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Cell Painting Gallery: an open resource for image-based profiling

Nature Methods, Journal Year: 2024, Volume and Issue: 21(10), P. 1775 - 1777

Published: Sept. 2, 2024

Language: Английский

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Applications of Artificial Intelligence, Deep Learning, and Machine Learning to Support the Analysis of Microscopic Images of Cells and Tissues

Journal of Imaging, Journal Year: 2025, Volume and Issue: 11(2), P. 59 - 59

Published: Feb. 15, 2025

Artificial intelligence (AI) transforms image data analysis across many biomedical fields, such as cell biology, radiology, pathology, cancer and immunology, with object detection, feature extraction, classification, segmentation applications. Advancements in deep learning (DL) research have been a critical factor advancing computer techniques for mining. A significant improvement the accuracy of detection algorithms has achieved result emergence open-source software innovative neural network architectures. Automated now enables extraction quantifiable cellular spatial features from microscope images cells tissues, providing insights into organization various diseases. This review aims to examine latest AI DL mining microscopy images, aid biologists who less background knowledge machine (ML), incorporate ML models focus images.

Language: Английский

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A review on computational tools for antidiabetic herbs research

Discover Chemistry., Journal Year: 2025, Volume and Issue: 2(1)

Published: April 15, 2025

Language: Английский

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Explainable biology for improved therapies in precision medicine: AI is not enough

Best Practice & Research Clinical Rheumatology, Journal Year: 2024, Volume and Issue: unknown, P. 102006 - 102006

Published: Sept. 1, 2024

Language: Английский

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Biophotonics in Microsystems

Elsevier eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский

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Generative AI in Drug Designing: Current State-of-the-Art and Perspectives

Studies in computational intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 427 - 463

Published: Jan. 1, 2024

Language: Английский

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