AI Medical Compendium Topic

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

Spheroids, Cellular

Showing 11 to 20 of 20 articles

Clear Filters

Robotic printing and drug testing of 384-well tumor spheroids.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A major impediment to anti-cancer drug development is the lack of a reliable and inexpensive tumor model to test the efficacy of candidate compounds. This need has emerged due to the insufficiency of widely-used monolayer cultures to predict drug eff...

Hybrid-Actuating Macrophage-Based Microrobots for Active Cancer Therapy.

Scientific reports
Using macrophage recruitment in tumors, we develop active, transportable, cancer theragnostic macrophage-based microrobots as vector to deliver therapeutic agents to tumor regions. The macrophage-based microrobots contain docetaxel (DTX)-loaded poly-...

Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning.

Analytical chemistry
Multicellular spheroids (hereinafter referred to as spheroids) are 3D biological models. The metabolomic profiles inside spheroids provide crucial information reflecting the molecular phenotypes and microenvironment of cells. To study the influence o...

Automating a Magnetic 3D Spheroid Model Technology for High-Throughput Screening.

SLAS technology
Affordable and physiologically relevant three-dimensional (3D) cell-based assays used in high-throughput screening (HTS) are on the rise in early drug discovery. These technologies have been aided by the recent adaptation of novel microplate treatmen...

Deep learning guided image-based droplet sorting for on-demand selection and analysis of single cells and 3D cell cultures.

Lab on a chip
Uncovering the heterogeneity of cellular populations and multicellular constructs is a long-standing goal in fields ranging from antimicrobial resistance to cancer research. Emerging technology platforms such as droplet microfluidics hold the promise...

How to Apply Supervised Machine Learning Tools to MS Imaging Files: Case Study with Cancer Spheroids Undergoing Treatment with the Monoclonal Antibody Cetuximab.

Journal of the American Society for Mass Spectrometry
As the field of mass spectrometry imaging continues to grow, so too do its needs for optimal methods of data analysis. One general need in image analysis is the ability to classify the underlying regions within an image, as healthy or diseased, for e...

Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study.

Scientific reports
The last two decades saw the establishment of three-dimensional (3D) cell cultures as an acknowledged tool to investigate cell behaviour in a tissue-like environment. Cells growing in spheroids differentiate and develop different characteristics in c...

Deep-LUMEN assay - human lung epithelial spheroid classification from brightfield images using deep learning.

Lab on a chip
Three-dimensional (3D) tissue models such as epithelial spheroids or organoids have become popular for pre-clinical drug studies. In contrast to 2D monolayer culture, the characterization of 3D tissue models from non-invasive brightfield images is a ...