AIMC Topic: Cell Differentiation
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A deep learning algorithm to translate and classify cardiac electrophysiology.
eLife
Jul 2, 2021
The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network ...
Action Potentials
Cell Differentiation
Models, Biological
Sulfonamides
Algorithms
Humans
Computer Simulation
Deep Learning
Electrophysiological Phenomena
Induced Pluripotent Stem Cells
Electrophysiologic Techniques, Cardiac
Phenethylamines
ERG1 Potassium Channel
Myocytes, Cardiac
Gene Expression Regulation
A deep-learning based artificial intelligence (AI) approach for differentiation of clear cell renal cell carcinoma from oncocytoma on multi-phasic MRI.
Clinical imaging
Jun 18, 2021
PURPOSE: To investigate the diagnostic performance of a deep convolutional neural network for differentiation of clear cell renal cell carcinoma (ccRCC) from renal oncocytoma.
Regression plane concept for analysing continuous cellular processes with machine learning.
Nature communications
May 5, 2021
Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce the Regression Plane (RP), a user-friendly discovery tool e...
Label-free quality control and identification of human keratinocyte stem cells by deep learning-based automated cell tracking.
Stem cells (Dayton, Ohio)
Mar 30, 2021
Stem cell-based products have clinical and industrial applications. Thus, there is a need to develop quality control methods to standardize stem cell manufacturing. Here, we report a deep learning-based automated cell tracking (DeepACT) technology fo...
Integrated functional neuronal network analysis of 3D silk-collagen scaffold-based mouse cortical culture.
STAR protocols
Jan 25, 2021
Bioengineered 3D tunable neuronal constructs are a versatile platform for studying neuronal network functions, offering numerous advantages over existing technologies and providing for the discovery of new biological insights. Functional neural netwo...
Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status.
Computers in biology and medicine
Dec 11, 2020
Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human tissue cells. They offer new opportunities for personalized medicine and drug screening. This requires large quantities of high quality hiPSCs, obtai...
Machine Learning of Hematopoietic Stem Cell Divisions from Paired Daughter Cell Expression Profiles Reveals Effects of Aging on Self-Renewal.
Cell systems
Dec 8, 2020
Changes in stem cell activity may underpin aging. However, these changes are not completely understood. Here, we combined single-cell profiling with machine learning and in vivo functional studies to explore how hematopoietic stem cell (HSC) division...
Neuronal differentiation strategies: insights from single-cell sequencing and machine learning.
Development (Cambridge, England)
Dec 8, 2020
Neuronal replacement therapies rely on the differentiation of specific cell types from embryonic or induced pluripotent stem cells, or on the direct reprogramming of differentiated adult cells via the expression of transcription factors or signaling...
Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation.
Nature communications
Dec 7, 2020
The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell...
Recognized trophoblast-like cells conversion from human embryonic stem cells by BMP4 based on convolutional neural network.
Reproductive toxicology (Elmsford, N.Y.)
Nov 26, 2020
The use of models of stem cell differentiation to trophoblastic cells provides an effective perspective for understanding the early molecular events in the establishment and maintenance of human pregnancy. In combination with the newly developed deep...
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