AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cell Differentiation

Showing 81 to 90 of 108 articles

Clear Filters

OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors.

Briefings in bioinformatics
Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer libra...

Detection and Weak Segmentation of Masses in Gray-Scale Breast Mammogram Images Using Deep Learning.

Yonsei medical journal
PURPOSE: In this paper, we propose deep-learning methodology with which to enhance the mass differentiation performance of convolutional neural network (CNN)-based architecture.

[Naringenin promotes osteogenic differentiation of BMSCs via SDF-1α/CXCR4 signaling axis].

Shanghai kou qiang yi xue = Shanghai journal of stomatology
PURPOSE: To explore the influence of naringenin on osteogenic differentiation of bone mesenchymal stem cells(BMSCs), and the role of SDF-1α/CXCR4 signaling axis in the osteogenic differentiation by naringenin.

Application of a deep learning-based image analysis and live-cell imaging system for quantifying adipogenic differentiation kinetics of adipose-derived stem/stromal cells.

Adipocyte
Quantitative methods for assessing differentiative potency of adipose-derived stem/stromal cells may lead to improved clinical application of this multipotent stem cell, by advancing our understanding of specific processes such as adipogenic differen...

Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set.

Blood
Biomedical applications of deep learning algorithms rely on large expert annotated data sets. The classification of bone marrow (BM) cell cytomorphology, an important cornerstone of hematological diagnosis, is still done manually thousands of times e...

Applying Machine Learning to Stem Cell Culture and Differentiation.

Current protocols
Machine learning techniques are increasingly becoming incorporated into biological research workflows in a variety of disciplines, most notably cancer research and drug discovery. Efforts in stem cell research comparatively lag behind. We detail key ...

Deep neural net tracking of human pluripotent stem cells reveals intrinsic behaviors directing morphogenesis.

Stem cell reports
Lineage tracing is a powerful tool in developmental biology to interrogate the evolution of tissue formation, but the dense, three-dimensional nature of tissue limits the assembly of individual cell trajectories into complete reconstructions of devel...

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

The Journal of clinical investigation
Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and noninvasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodolo...