Deep Morphology Learning Enhances Ex Vivo Drug Profiling-Based Precision Medicine.
Tim HeinemannChristoph KornauthYannik SeverinGregory I VladimerTea PemovskaEmir HadzijusufovicHermine AgisMaria-Theresa KrauthWolfgang R SperrPeter ValentUlrich JägerIngrid Simonitsch-KluppGiulio Superti-FurgaPhilipp Bernhard StaberBerend SnijderPublished in: Blood cancer discovery (2022)
We have recently demonstrated that image-based drug screening in patient samples identifies effective treatment options for patients with advanced blood cancers. Here we show that using deep learning to identify malignant and nonmalignant cells by morphology improves such screens. The presented workflow is robust, automatable, and compatible with clinical routine. This article is highlighted in the In This Issue feature, p. 476.
Keyphrases
- deep learning
- genome wide
- induced apoptosis
- machine learning
- artificial intelligence
- convolutional neural network
- cell cycle arrest
- case report
- adverse drug
- high throughput
- clinical practice
- single cell
- electronic health record
- emergency department
- drug induced
- cell death
- signaling pathway
- oxidative stress
- young adults