AIMC Topic: Induced Pluripotent Stem Cells

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

The Journal of clinical investigation Feb 3, 2020
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...
Humans Deep Learning Image Processing, Computer-Assisted Cell Differentiation Microscopy Retinal Pigment Epithelium Induced Pluripotent Stem Cells
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Human Induced Pluripotent Stem Cell Reprogramming Prediction in Microscopy Images using LSTM based RNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
We present a LSTM (Long Short-Term Memory) based RNN (recurrent neural network) method for predicting human induced Pluripotent Stem (hiPS) cells in the reprogramming process. The method uses a trained LSTM network by time-lapse microscopy images to ...
Humans Neural Networks, Computer Cellular Reprogramming Microscopy Induced Pluripotent Stem Cells
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[Challenges to Improve the Prediction Accuracy of the Non-clinical Tests for Human CNS Adverse Effects: Potentials of Artificial Intelligence and Human ESC/iPSC-derived Neurons].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan Jan 1, 2018
Humans Artificial Intelligence Drug Discovery Cell Differentiation Drug Evaluation, Preclinical Neurons Central Nervous System Agents Neuroimaging Animal Testing Alternatives Induced Pluripotent Stem Cells Human Embryonic Stem Cells
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