AIMC Topic: Cell Differentiation

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Cellograph: a semi-supervised approach to analyzing multi-condition single-cell RNA-sequencing data using graph neural networks.

BMC bioinformatics Jan 15, 2024
With the growing number of single-cell datasets collected under more complex experimental conditions, there is an opportunity to leverage single-cell variability to reveal deeper insights into how cells respond to perturbations. Many existing approac...
Neural Networks, Computer RNA Data Visualization Cluster Analysis Cell Differentiation
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Uncovering hidden treasures: Mapping morphological changes in the differentiation of human mesenchymal stem cells to osteoblasts using deep learning.

Micron (Oxford, England : 1993) Jan 8, 2024
Deep Learning (DL) is becoming an increasingly popular technology being employed in life sciences research due to its ability to perform complex and time-consuming tasks with significantly greater speed, accuracy, and reproducibility than human resea...
Humans Reproducibility of Results Mesenchymal Stem Cells Osteoblasts Deep Learning Cell Differentiation
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Quantitative Modeling of Stemness in Single-Cell RNA Sequencing Data: A Nonlinear One-Class Support Vector Machine Method.

Journal of computational biology : a journal of computational molecular cell biology Nov 28, 2023
Intratumoral heterogeneity and the presence of cancer stem cells are challenging issues in cancer therapy. An appropriate quantification of the stemness of individual cells for assessing the potential for self-renewal and differentiation from the cel...
Humans Cell Differentiation Sequence Analysis, RNA Support Vector Machine Neoplasms Single-Cell Analysis
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Recognition and reconstruction of cell differentiation patterns with deep learning.

PLoS computational biology Oct 27, 2023
Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to rep...
Animals Deep Learning Neural Networks, Computer Algorithms Cell Differentiation Mice Models, Theoretical
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Leukocyte differentiation in bronchoalveolar lavage fluids using higher harmonic generation microscopy and deep learning.

PloS one Jun 27, 2023
BACKGROUND: In diseases such as interstitial lung diseases (ILDs), patient diagnosis relies on diagnostic analysis of bronchoalveolar lavage fluid (BALF) and biopsies. Immunological BALF analysis includes differentiation of leukocytes by standard cyt...
Bronchoalveolar Lavage Cell Differentiation Leukocytes Humans Deep Learning Bronchoalveolar Lavage Fluid Leukocyte Count Lung Diseases, Interstitial Microscopy
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Morphological feature recognition of different differentiation stages of induced ADSCs based on deep learning.

Computers in biology and medicine Apr 13, 2023
In order to accurately identify the morphological features of different differentiation stages of induced Adipose Derived Stem Cells (ADSCs) and judge the differentiation types of induced ADSCs, a morphological feature recognition method of different...
Deep Learning Image Processing, Computer-Assisted Cell Differentiation Diagnostic Imaging Neural Networks, Computer
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Artificial intelligence of digital morphology analyzers improves the efficiency of manual leukocyte differentiation of peripheral blood.

BMC medical informatics and decision making Mar 29, 2023
BACKGROUND AND OBJECTIVE: Morphological identification of peripheral leukocytes is a complex and time-consuming task, having especially high requirements for personnel expertise. This study is to investigate the role of artificial intelligence (AI) i...
Leukocytes Humans Cell Differentiation Artificial Intelligence Sensitivity and Specificity
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Rapid Identification of Infectious Pathogens at the Single-Cell Level via Combining Hyperspectral Microscopic Images and Deep Learning.

Cells Jan 19, 2023
Identifying infectious pathogens quickly and accurately is significant for patients and doctors. Identifying single bacterial strains is significant in eliminating culture and speeding up diagnosis. We present an advanced optical method for the rapid...
Deep Learning Cell Differentiation Hyperspectral Imaging Humans Communicable Diseases
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Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches.

Cells Jan 4, 2023
Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the produc...
Humans Induced Pluripotent Stem Cells Cell Differentiation Artificial Intelligence Retinal Pigment Epithelium Deep Learning
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Predicting multipotency of human adult stem cells derived from various donors through deep learning.

Scientific reports Dec 14, 2022
Adult stem cell-based therapeutic approaches have great potential in regenerative medicine because of their immunoregulatory properties and multidifferentiation capacity. Nevertheless, the outcomes of stem cell‑based therapies to date have shown inco...
Stem Cells Adult Cell Differentiation Deep Learning Regenerative Medicine Humans Adult Stem Cells
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